• Title/Summary/Keyword: On-machine Measurement

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The Study on Measurement of Relative Conversion Factor in X-ray Image Intensifier (X선영상증배관의 상대변환계수 측정에 관한 검토)

  • Kim, Sung-Chul;Shin, Sung-Ill;Lee, Sun-Sook;Huh, Joon;Kim, Sung-Soo
    • Journal of radiological science and technology
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    • v.20 no.2
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    • pp.28-33
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    • 1997
  • For the Evaluation of X-ray image intensifier, we measured radiation dose at input of I. I., brightness and fluorescence at output of I. I. by using X-ray exposure meter, optometer and fluorescence meter for the relative conversion factor. Especially, by using fluorescence meter, we could easily get relative conversion factor without having regulated machine by JIS. Since using, the quality of image intensifier is going down. Consequently, it needs continuous quality maintenance.

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New Current Measurement Device in Resistance Spot Welding by Using the Ring Deformation (링의 변형을 이용한 저항용접 전류측정장치의 개발)

  • Park, S.W.;Na, S.J.
    • Proceedings of the KWS Conference
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    • 1990.11a
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    • pp.82-86
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    • 1990
  • A new method was investigated to measure the high current in resistance welding processes. A measuring unit was developed by using a strain gage attached on the outer surface of a steel ring. The steel ring was placed around a section of the secondary loop of the welding machine, and was deformed by electro-magnetic forces induced by the high welding current. The circumferential constituent of the ring deformation was then used to obtain a signal voltage proportional to the secondary welding current. The strain gage signal of ring deformation is enough to determine the welding current in resistance spot welding, especially when welded with direct current.

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Translation:Mapping and Evaluation (번역: 대응과 평가)

  • 장석진
    • Language and Information
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    • v.2 no.1
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    • pp.1-41
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    • 1998
  • Evaluation of multilingual translation fundamentally involves measurement of meaning equivalences between the formally mapped discourses/texts of SL(source language) and TL(target language) both represented by a metalanguage called IL(interlingua). Unlike a usaal uni-directional MT(machine translation) model(e.g.:SL $\rightarrow$ analysis $\rightarrow$ transfer $\rightarrow$ generation $\rightarrow$ TL), a bi-directional(by 'negotiation') model(i.e.: SL $\rightarrow$ IL/S $\leftrightarrow$ IL $\leftrightarrow$ IL/T \leftarrow TL) is proposed here for the purpose of evaluating multilingual, not merely bilingual, translation. The IL, as conceived of in this study, is an English-based predicate logic represented in the framework of MRS(minimal recursion semantics), an MT-oriented off-shoot of HPSG(Head-driven Phrase Structure Grammar). In addition, a list of semantic and pragmatic checkpoints are set up, some being optional depending on the kind and use of the translation, so sa to have the evaluation of translation fine-grained by computing matching or mismatching of such checkpoints.

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Performance measurement method for Host OS and Guest OS of Virtual Machine in simultaneously use environment (가상머신의 Host OS와 Guest OS의 동시 사용을 위한 성능 측정 방법)

  • On, Jin-Ho;U, Su-Jeong;Kim, Won-Young;Choi, Wan;Lee, Moon-Kun
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10b
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    • pp.269-273
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    • 2007
  • 하드웨어의 급속한 성능증가와 서버의 동적인 활용을 위하여 가상화 기술의 연구 및 개발이 급격히 증가하고 있다. 이러한 가상화 기술의 성능을 측정하기 위한 기존의 방법들은 가상머신에 설치된 Guest OS 만을 고려하거나, 시스템이 설치된 하드웨어를 대상으로 통합적으로 평가되었다. 하지만, 여러 개의 Guest OS를 사용하는 경우/ Host OS와 Guest OS가 서로 통신할 경우에서는 이와 같은 측정 방법에 문제점이 발생한다. 본 논문은 Host OS와 Guest OS가 서로 통신할 경우 발생하는 Host OS의 자원 사용을 평가하여 Guest OS의 성능에 미치는 영향을 분석하고, 이러한 영향을 정확히 분석하기 위한 방법을 제안한다.

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Deep-learning based In-situ Monitoring and Prediction System for the Organic Light Emitting Diode

  • Park, Il-Hoo;Cho, Hyeran;Kim, Gyu-Tae
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.4
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    • pp.126-129
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    • 2020
  • We introduce a lifetime assessment technique using deep learning algorithm with complex electrical parameters such as resistivity, permittivity, impedance parameters as integrated indicators for predicting the degradation of the organic molecules. The evaluation system consists of fully automated in-situ measurement system and multiple layer perceptron learning system with five hidden layers and 1011 perceptra in each layer. Prediction accuracies are calculated and compared depending on the physical feature, learning hyperparameters. 62.5% of full time-series data are used for training and its prediction accuracy is estimated as r-square value of 0.99. Remaining 37.5% of the data are used for testing with prediction accuracy of 0.95. With k-fold cross-validation, the stability to the instantaneous changes in the measured data is also improved.

Wind engineering for high-rise buildings: A review

  • Zhu, Haitao;Yang, Bin;Zhang, Qilin;Pan, Licheng;Sun, Siyuan
    • Wind and Structures
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    • v.32 no.3
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    • pp.249-265
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    • 2021
  • As high-rise buildings become more and more slender and flexible, the wind effect has become a major concern to modern buildings. At present, wind engineering for high-rise buildings mainly focuses on the following four issues: wind excitation and response, aerodynamic damping, aerodynamic modifications and proximity effect. Taking these four issues of concern in high-rise buildings as the mainline, this paper summarizes the development history and current research progress of wind engineering for high-rise buildings. Some critical previous work and remarks are listed at the end of each chapter. From the future perspective, the CFD is still the most promising technique for structural wind engineering. The wind load inversion and the introduction of machine learning are two research directions worth exploring.

A Study on Object Classification Using IR-UWB (IR-UWB를 이용한 물체 분류에 관한 연구)

  • Gam, Ji-Hyeon;Jeong, Jae-Hoon;Byun, Gi-Sig;Kim, Gwan-Hyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.88-90
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    • 2018
  • There are many studies on IR-UWB Radar. A number of studies have been conducted on the Personnel count and measurement distance to person, mainly using IR-UWB. In this paper, however, we use IR-UWB Radar to distinguish objects. In order to distinguish these objects, in this paper, the IR-UWB radar is operated by positioning the object at a certain distance and the object is classified by using the size and shape of the wave reflected by the object. To distinguish objects using only the size and shape of these waveforms, SVM (Support Vector Machine) was used to classify objects by learning shape and size of waveforms. In this paper, we show that the size and shape of the waveform received by the IR-UWB Radar can be identified by SVM pattern learning.

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PREDICTION OF RESIDUAL STRESS PROFILE IN SINGLE-SIDED BUTT WELD USING COMPLIANCE METHOD

  • Kim, Yooil;Jeon, Yu-Chul;Kang, Joong-Kyoo;Han, Yong-Sub
    • Proceedings of the KWS Conference
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    • 2002.10a
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    • pp.156-161
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    • 2002
  • It depends on the joint configuration, dimensions and constraints on the joint whether the residual stress at the root of single-sided butt weld is tensile or not. Therefore, recommendation is generally made that high R ratio should be used in the fatigue test of this type of joint in order to prevent excessively long life caused by compressive residual stress. in this research, the residual stress profile in butt weld joint was obtained through compliance method, using successive extension of a slot and measurement of the variation of strain during the slot extension. The residual stress profile was firstly assumed to be the linear summation of Legendre polynomials up to 9th order excluding 0th and 1st order. Strain variation on the surface was measured while the slot was being extended by cutting to find out the 8 unknown coefficients of each polynomial tenn. The cut was made by the electric discharge machine. It was concluded that the residual stress near the surface stayed positive, however, it turned into the negative value as soon as it passed through 2 or 3 mm depth. Several fatigue tests were also carried out under zero stress ratio. Test results showed that fatigue life coincides well with the design cuive of butt joint in British Standards, which supports that it is tensile residual stress that exists near the weld root.

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Development of Octagonal Ring Load Cell Based on Strain Rings (스트레인 링 이론 기반의 팔각링 로드셀 개발)

  • Kim, Joong-Seon;Jo, Hyeong-Geun;Wang, Duck-Hyun
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.17 no.4
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    • pp.97-103
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    • 2018
  • Force is a crucial element to be measured in various industries, especially the machine tool industry. Mega units of force are required in fields such as the heavy and ship industries. Micro/nano units of force are required for microparticles. The detection of force generates a physical transformation due to the force imposed from the outside, atlrnd electrical voltage signals are obtained from the system. For the detection of force, an octagonal ring load cell based on circular ring theory is designed and produced. To design the octagonal strain ring, theoretical values with data from the ANSYS program are compared to determine the size of the octagonal strain ring. An octagonal strain ring of the chosen size is made with the SCM415 material. The strain gauges are attached to the octagonal strain ring, designed to construct a full Wheatstone bridge. The LabVIEW program is used to measure the data, and strain values are found. With the octagonal ring load cell completed in this way, experiments are conducted by imposing forces on the tangential axis and radial axis. Experiments are performed to verify if the octagonal ring load cell conducts measurements properly, and theoretical values are analyzed to find any differences. The data will later be used in further research to develop a machine-tool dynamometer.

Improving the Performance of Machine Learning Models for Anomaly Detection based on Vibration Analog Signals (진동 아날로그 신호 기반의 이상상황 탐지를 위한 기계학습 모형의 성능지표 향상)

  • Jaehun Kim;Sangcheon Eom;Chulsoon Park
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.47 no.2
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    • pp.1-9
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    • 2024
  • New motor development requires high-speed load testing using dynamo equipment to calculate the efficiency of the motor. Abnormal noise and vibration may occur in the test equipment rotating at high speed due to misalignment of the connecting shaft or looseness of the fixation, which may lead to safety accidents. In this study, three single-axis vibration sensors for X, Y, and Z axes were attached on the surface of the test motor to measure the vibration value of vibration. Analog data collected from these sensors was used in classification models for anomaly detection. Since the classification accuracy was around only 93%, commonly used hyperparameter optimization techniques such as Grid search, Random search, and Bayesian Optimization were applied to increase accuracy. In addition, Response Surface Method based on Design of Experiment was also used for hyperparameter optimization. However, it was found that there were limits to improving accuracy with these methods. The reason is that the sampling data from an analog signal does not reflect the patterns hidden in the signal. Therefore, in order to find pattern information of the sampling data, we obtained descriptive statistics such as mean, variance, skewness, kurtosis, and percentiles of the analog data, and applied them to the classification models. Classification models using descriptive statistics showed excellent performance improvement. The developed model can be used as a monitoring system that detects abnormal conditions of the motor test.