• Title/Summary/Keyword: 오차 인자 분석

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연삭 가공에 있어서 열변형으로 인한 영상오차에 관한 연구

  • 박구하;홍순익;김남경;송지복
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1992.04a
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    • pp.120-124
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    • 1992
  • 평면 연삭가공에 있어서 피삭재의 진직도의 제어는 정밀계측기와 같은 정밀기기의 제작에 중요한 문재중 하나이다. 본 연구에서는 연삭작업 능률을 향상시키기 위해 고 능률 단공정 가공시 발생할 수 있는 피삭재의 열변형기등을 유한요소법으로 밝힌것을 기초로 실험과의 타당성 여부를 검토하고, 고능률 연삭시 형상오차에 미치는 여러가지인자의 영향을 조사하였으며, 회귀분석에의해 형상오차의 추정치를 예측하였다.

Error Analysis of SOC Estimation using Coulomb Counting Method (전류적산법을 이용한 SOC 추정 시 오차 발생 요인 분석)

  • Cho, Yong-Ki;Ahn, Jung-Hoon;Ryu, Seung-Hee;Lee, Byoung-Kuk
    • Proceedings of the KIPE Conference
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    • 2013.11a
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    • pp.216-217
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    • 2013
  • 본 논문에서는 전류적산법을 이용한 배터리 SOC 추정에 있어 오차를 발생시키는 원인들에 대한 이론적인 분석을 통하여 주요 인자들 중 전류센서, 스케일 변환회로, ADC에서 발생 가능한 오차 발생 요인을 고려한다. 그리고 오차를 반영한 시뮬레이션으로 BMS모델을 구현하여 실제 실험과의 정확성을 판단하고, 오차 발생 비중을 규명한다.

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Regional drought characteristics analysis of natural drought index (자연가뭄지수의 지역별 가뭄특성분석)

  • Kim, Seon-Ho;So, Jae-Min;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.149-149
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    • 2016
  • 최근 전 세계적으로 이상기후가 발생하고 있으며, 국내에서도 과거에 경험하지 못했던 자연재해가 빈번하게 발생하고 있는 추세이다. 가뭄은 홍수와 더불어 그 피해가 가장 큰 자연재해 중 하나이며, 장주기적이고 광역적으로 발생함에 따라 구체적인 발생시기, 장소, 원인을 파악하는 것이 어렵다. 그동안 국내에서는 가뭄극복을 위해 다양한 대책을 마련해 왔음에도 불구하고 가뭄피해는 지속적으로 증가하고 있다. 실례로 2014~2015 가뭄으로 소양강 댐은 역대 최저수위를 기록하였으며, 일부 지역에서는 제한급수, 농업용수 부족 피해가 발생한 바 있다. 이처럼 가뭄으로 인한 피해는 기후 변화의 영향으로 더욱 빈번할 것이라는 보고가 있어 가뭄해석을 위한 지속적인 노력이 필요하다. 가뭄해석에는 일반적으로 가뭄의 시작, 끝, 지속기간, 발생간격, 누적심도 등을 사용하며, 이를 가뭄특성인자라고 한다. 따라서 본 연구에서는 인위적인 시설물의 영향을 배제한 자연가뭄지수(Natural Drought Index, NDI)를 이용하여 국내 5개 행정구역의 지역별 가뭄특성을 분석하였다. 자연가뭄지수의 산정을 위해 입력자료는 3개월 누적강수량, 누적유출량, 평균토양수분량을 사용하였으며, 강수량은 국내 ASOS 59개 지점 자료, 유출량 및 토양수분량은 지표수문해석모형의 결과를 이용하였다. 가뭄특성 분석기간은 1977~2012년이며, 가뭄특성인자는 가뭄의 시작, 끝, 지속기간, 발생간격을 활용하였다. 과거 가뭄피해사례와, SPI, SRI, SSI 및 NDI의 가뭄특성인자를 비교하였으며, 정량적 비교를 위해 평균오차, 평균절대오차를 사용하였다. 가뭄특성인자 분석 결과 NDI는 가뭄의 시작과 끝을 가장 정확하게 반영하였다. 가뭄의 지속기간은 NDI, 발생간격은 NDI와 SPI가 정확한 것으로 나타났다. 자연가뭄지수는 단일변량 가뭄지수에 비해 지역적 가뭄특성을 정확하게 재현한다는 점에서 추후 가뭄감시에 유용하게 활용될 것으로 판단된다.

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Tolerance Factor Analysis of Flexible Pedestrian Legform Impactor Test (신형 하부다리 모형 시험 결과에 영향을 미치는 오차 인자 분석)

  • Lee, Yonghoon;Kim, Hanseung;Jang, Sungjae
    • Journal of Auto-vehicle Safety Association
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    • v.6 no.2
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    • pp.43-48
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    • 2014
  • The flexible pedestrian legform impactor(Flex-PLI) consisting of a flexible femur and tibia will be tested for pedestrian protection by global technical regulation(GTR) within the next couple of years as a replacement for the existing transport research laboratory(TRL) legform impactor. In this study, a computer aided engineering(CAE) model was used to perform the effect analysis of each injury with regard to the changes in tolerance factors with the baseline results without tolerance. The tolerance factors were the height of impactor from ground reference line, initial velocity of impactor and rotation of impactor.

Optimization of Soil Contamination Distribution Prediction Error using Geostatistical Technique and Interpretation of Contributory Factor Based on Machine Learning Algorithm (지구통계 기법을 이용한 토양오염 분포 예측 오차 최적화 및 머신러닝 알고리즘 기반의 영향인자 해석)

  • Hosang Han;Jangwon Suh;Yosoon Choi
    • Economic and Environmental Geology
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    • v.56 no.3
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    • pp.331-341
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    • 2023
  • When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.

Error Budget Analysis of Pseudorange for Improving the GPS Positioning Accuracy (GPS 위치정확도 향상을 위한 의사거리 오차의 분석에 관한 연구)

  • Kim, Yong-Il;Kim, Dong-Hyun;Kim, Byung-Guk
    • Journal of Korean Society for Geospatial Information Science
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    • v.4 no.2 s.8
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    • pp.79-90
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    • 1996
  • It is well known that point positioning using a C/A-code receiver is severely biased by errors in pseudorange. This paper shows the procedures of quantitive analysis for several error elements and that some methods to monitor SA(selective availability) of witch process is not opened are proposed. It is possible to verify the effects of SA in the Doppler shift and receiver clock drift variation. Easy methods to reduce SA effects are to fit second order polynomials for the one and a linear function for the other. With periodic autocorrelation functions. SA effects are analyzed and first order Gauss-Markov process parameters are decided.

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Reliability and Validity of PWI(Psychosocial Wellbeing Index) (Psychosocial Wellbeing Index의 신뢰도 및 타당도)

  • Lee, Chae-Yong;Lee, Jong-Young
    • Journal of Preventive Medicine and Public Health
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    • v.29 no.2 s.53
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    • pp.255-264
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    • 1996
  • To study reliability and validity of PWI, this newly developed self-administered questionnaire which measures stress, was given to medical students. All respondent(133) were followed 4 weeks later and 92 were retested. Cronbach's $\alpha$ coefficient of data was 0.93. Test-retest reliability measured by Pearson's correlation coefficient was 0.72(P<0.01). Exploratory factor analysis(EFA) performed by principal axis factor method without iteration and by varimax rotation explored 13 principal components(eigenvalues > 1). After exploring 4 factor structure according to previous study results, factor 1 showed good agreement but other factors did not. Confirmatory factor analysis(CFA) showed poor fit of 4 factor model to data. In the further study, it may be considered to model that has unidimensional factor structure.

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Quantitative Surface Analysis of Co-Ni and Au-Cu alloys by XPS and SIMS (XPS와 SIMS에 의한 Co-Ni과 Au-Cu 합금표면 정량분석 연구)

  • 김경중;문대원;이광우
    • Journal of the Korean Vacuum Society
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    • v.1 no.1
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    • pp.106-114
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    • 1992
  • Abstract-Quantitative surface analysis of Co-Ni and Au-Cu alloys by XPS and SIMS was studied. For Co-Ni alloy, quantitative XPS analysis could be done within 1-2% relative error with pure element standards without any correction. For Au-Cu, quantitative XPS analysis was not possible without any correction. But it could be done with standard alloys of various composition within 1-2% relative error. Without standard alloys, Au-Cu alloys could be analyzed by XPS within 10% relative error with pure element standards. For SIMS analysis of Co-Ni alloys, the relative secondary ion yields of Co+/Nit has linear relation with ratio of each composition so that quantitative SIMS analysis was possible for Co-Ni alloys. Preliminary results of XPS round robin test of VAMAS-SCA Japan Project are given.

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Analysis of Statistical Characteristics of Annual Precipitation in Korea Using Data Screeening Technique (데이터 스크린 기법을 이용한 연강수량의 통계적 특성 분석)

  • Jeung, Se-Jin;Lim, Ga-Kyun;Kim, Byung-Sik
    • Journal of Korean Society of Disaster and Security
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    • v.13 no.3
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    • pp.15-28
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    • 2020
  • Hydrological data is very important in understanding the hydrological process and identifying its characteristics to protect human life and property from natural disasters. In particular, hydrological analysis are often performed assuming that hydrological data are stationary. However, recently climate change has raised the issue of climate stationary, and it is necessary to analyze the nonstationary of the climate. In this study, a method to analyze the stationarity of hydrological data was examined using the annual precipitation of 37 meteorological stations with long - term record data. Therefore, in this study, the stationary was determined by analyzing the persistence, trend, and stability using annual precipitation. Overall results showed that a trend was observed in 4 out of 37 stations, stable was investigated at 15 stations, and persistence was shown at 4 stations. In the stationary analysis using the annual precipitation data, 25 stations (67% of 37 stations) were nonstationary.

IRF performance prediction by analyzing of amplitude and phase errors for the wideband Chirp signal (광대역 첩 신호의 진폭 및 위상오차 분석을 통한 IRF 성능 분석)

  • Kim, Dong-Sik;Kim, Jong-Pil;Lee, Jong-Hwan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.44 no.2
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    • pp.131-138
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    • 2016
  • In this paper, we studied the IRF performances of the chirp signal used in the SAR system. The most important factors that degrade IRF performances are amplitude and phase errors. Each factor can be represented to linear, quadratic, random and ripple terms. That can be extracted by a quadratic polynomial curve fitting of chirp waveform. We analyzed the IRF performances by the error terms and supposed the minimum value of RF non-linearity to meet the specification of the PSLR and ISLR.