• 한국정밀공학회지
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• 제15권11호
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• pp.9-20
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• 1998

In recent manufacturing process, the increase of productivity has been attempted by reducing machining time with the increase of cutting force. However, the excessive increase of cutting force can cause tool breakage and have a bad effect on both manufacturing machine and workpiece. Thus, it is necessary to estimate and control the cutting force in real time during the process. In this study, use of disturbance observer is proposed for the indirect cutting force estimation. The estimated cutting force is used for the real-time control of feedrate, making the actual cutting force follow the reference force command. Since the suggested method does not need an expensive sensor like a dynamometer, the method is expected to be used practically. Since the actual cutting force follow the reference force, resulting the reducing of the machining time the increase of productivity are also expected, and the quality of cutting surface has been improved due to the adjusted feedrate. Besides, an actual constant cutting force guarantees the prevention of tool breakage. To show the effectiveness of the suggested cutting force control method, an experimental setup has been made without sensor and applied to several workpieces. Experiments show that the suggested method is effective to cutting force control of a CNC machining center.

• 대한기계학회논문집A
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• 제21권6호
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• pp.918-924
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• 1997

A method for measuring the accuracy of rotating objects was studied. Rotating axis errors are significant; such as the spindle error of a manufacturing machine which results in the surface roughness of machined work pieces. Three capacitance type displacement sensors were used to measure the rotating master ball position. The sensors were mounted to the three orthogonal points on the spindle axis. The measurement data were analyzed and shown for rotating spindle accuracy, not only for average roundness error but also for spindle volumetric positional error during the revolutions. This method is simple and economical for industrial field use with regular inspection of rotating machines using portable equipment. Measuring and analyzing time using this method takes only a couple of hours. This method can also measure microscopic amplitude and 3-dimensional direction of vibrating objects.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.307-310
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• 2000

Recently, the demand for the Floating, Production Storage, and Offloading facility(FPSO) which has some economic and technical advantages, has increased in offshore oil production areas. The basic characteristics of a 343,000 DWT class FPSO which is being built in Hyundai Heavy Industries and shall be installed in offshore Angola, is almost same as that of oil carriers. However, she do not have self-propulsion system, but has additional facilities for oil production and positioning system. Main noise source contributing to the cabin noise of the accommodation, are classified into the machine in the engine room and the deckhouse, HVAC system, and the topside equipments. In general, the noise regulation for the offshore structure is much severer than that of the common commercial ships and the maximum acceptable sound pressure level of cabins is specified in 45dB(A). This paper describes the procedure of noise analysis along with its results. Noise analysis has been carried out for the case of emergency diesel generator running condition and the case of normal production condition and the results has been compared with the measurement results of the first case. Based on the results, proper countermeasures to reduce excessive noise level has been applied considering the characteristics of sources and receiver spaces and can be satisfied the specifications at all spaces.

• Design & Manufacturing
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• 제14권4호
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• pp.25-39
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• 2020

In this study, an edge device that monitors the injection molding process by measuring the mold vibration(acceleration) signal and the mold surface temperature was developed and evaluated its performance. During injection molding, signals of the injection start, V/P switchover, and packing end sections were obtained through the measurement of the mold vibration and the injection time and packing time were calculated by using the difference between the times of the sections. Then, the mold closed and mold open signals were obtained using a magnetic hall sensor, and cycle time was calculated by using the time difference between the mold closed time each process. As a result of evaluating the performance by comparing the process data monitored by the edge device with the shot data recorded on the injection molding machine, the cycle time, injection time, and packing time showed very small error of 0.70±0.38%, 1.40±1.17%, and 0.69±0.82%, respectively, and the values close to the actual were monitored and the accuracy and reliability of the edge device were confirmed. In addition, it was confirmed that the mold surface temperature measured by the edge device was similar to the actual mold surface temperature.

• 시스템엔지니어링학술지
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• 제16권2호
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• pp.38-46
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• 2020

The accurate measurement of critical heat flux (CHF) in flow boiling is important for the safety requirement of the nuclear power plant to prevent sharp degradation of the convective heat transfer between the surface of the fuel rod cladding and the reactor coolant. In this paper, a System Engineering approach is used to develop a model that predicts the CHF using machine learning. The model is built using artificial neural network (ANN). The model is then trained, tested and validated using pre-existing database for different flow conditions. The Talos library is used to tune the model by optimizing the hyper parameters and selecting the best network architecture. Once developed, the ANN model can predict the CHF based solely on a set of input parameters (pressure, mass flux, quality and hydraulic diameter) without resorting to any physics-based model. It is intended to use the developed model to predict the DNBR under a large break loss of coolant accident (LBLOCA) in APR1400. The System Engineering approach proved very helpful in facilitating the planning and management of the current work both efficiently and effectively.

• Design & Manufacturing
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• 제15권4호
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• pp.8-13
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• 2021

A plastic roller for opening and closing the safety door of the injection molding machine was molded. The dimensional change of the measurement position of the roller was studied when the cooling time was applied differently among the molding conditions, and when the temperature of the coolant applied for mold cooling was also applied differently. Cooling times of 300 seconds and 400 seconds, hot and low-temperature coolant were applied. When the low-temperature coolant was applied, the measuring point of the roller shrank by 0.03 mm. However, when the high-temperature coolant was applied, the measuring point shrank by 0.3 mm. It was found that the application of low-temperature coolant among coolants was more suitable for the reference dimension of the molded article compared to the application of high-temperature coolant. Among the cooling water applied for the molding of plastic rollers, when high-temperature coolant is applied, the shrinkage rate measured immediately after ejection was smaller than when low-temperature coolant is applied. However, it was found that post shrinkage, which occurs over time, occurs much larger when high-temperature coolant is applied.

• Journal of the Korean Wood Science and Technology
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• 제31권3호
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• pp.35-41
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• 2003

The mechanical and physical properties of wood are strongly dependent upon the slope of grain. Specially, tensile strength is more severely affected by the slope of grain. Therefore, tension tests were performed on small thin wood samples made from Pinus radiata with varying the slope of grain. Determining the tensile strength for clear thin wood samples the other variabilities associated with material, size, drying, defects, etc were discarded. Slope of grain was measured by the slope of grain indicator and actual slope of grain was also determined by a protractor. Correlation coefficients between machine measured and actual slope of grain for 40 pieces of 2×20 mm, 300 mm long Pinus radiata were 0.84 for wide face measurement. Results also showed that tensile strength and MOE from stress wave tests decreased with increasing the slope of grain. This study did not establish a relationships for tensile strength and MOE from stress wave with slope of grain. However, the trends of MOEs from stress wave test with both slope of grain are agreed well with Hankinson's equation. Predicted tension strength curve by Hankinson's equation was also agreed well with the experimental data over the range from 0 to 13 degrees for slope of grain.

• Wind and Structures
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• 제36권6호
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Nuclear Engineering and Technology
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• 제56권4호
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• pp.1347-1356
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• 2024

Measuring the residual stress in the components in nuclear power plants is crucial to their safety evaluation. The instrumented indentation technique is a minimally invasive approach that can be conveniently used to determine the residual stress in structural materials in service. Because the indentation behavior of a structure with residual stresses is closely related to the elastic-plastic behavior of the indented material, an accurate understanding of the elastic-plastic behavior of the material is essential for evaluation of the residual stresses in the structures. However, due to the analytical problems associated with solving the elastic-plastic behavior, empirical equations with limited applicability have been used. In the present study, the impact of the non-equibiaxial residual stress state on indentation behavior was investigated using finite element analysis. In addition, a new nonequibiaxial residual-stress prediction methodology is proposed using a convolutional neural network, and the performance was validated. A more accurate residual-stress measurement will be possible by applying the proposed residual-stress prediction methodology in the future.

• 지능정보연구
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• 제26권1호
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• pp.23-45
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• 2020

기업의 경쟁력 확보를 위해 판별 알고리즘을 활용한 의사결정 역량제고가 필요하다. 하지만 대부분 특정 문제영역에는 적합한 판별 알고리즘이 어떤 것인지에 대한 지식은 많지 않아 대부분 시행착오 형식으로 최적 알고리즘을 탐색한다. 즉, 데이터셋의 특성에 따라 어떠한 분류알고리즘을 채택하는 것이 적합한지를 판단하는 것은 전문성과 노력이 소요되는 과업이었다. 이는 메타특징(Meta-Feature)으로 불리는 데이터셋의 특성과 판별 알고리즘 성능과의 연관성에 대한 연구가 아직 충분히 이루어지지 않았기 때문이며, 더구나 다중 클래스(Multi-Class)의 특성을 반영하는 메타특징에 대한 연구 또한 거의 이루어진 바 없다. 이에 본 연구의 목적은 다중 클래스 데이터셋의 메타특징이 판별 알고리즘의 성능에 유의한 영향을 미치는지에 대한 실증 분석을 하는 것이다. 이를 위해 본 연구에서는 다중 클래스 데이터셋의 메타특징을 데이터셋의 구조와 데이터셋의 복잡도라는 두 요인으로 분류하고, 그 안에서 총 7가지 대표 메타특징을 선택하였다. 또한, 본 연구에서는 기존 연구에서 사용하던 IR(Imbalanced Ratio) 대신 시장집중도 측정 지표인 허핀달-허쉬만 지수(Herfindahl-Hirschman Index, HHI)를 메타특징에 포함하였으며, 역ReLU 실루엣 점수(Reverse ReLU Silhouette Score)도 새롭게 제안하였다. UCI Machine Learning Repository에서 제공하는 복수의 벤치마크 데이터셋으로 다양한 변환 데이터셋을 생성한 후에 대표적인 여러 판별 알고리즘에 적용하여 성능 비교 및 가설 검증을 수행하였다. 그 결과 대부분의 메타특징과 판별 성능 사이의 유의한 관련성이 확인되었으며, 일부 예외적인 부분에 대한 고찰을 하였다. 본 연구의 실험 결과는 향후 메타특징에 따른 분류알고리즘 추천 시스템에 활용할 것이다.