• 제목/요약/키워드: Geometric errors

검색결과 345건 처리시간 0.029초

STATIONARY $\beta-MIXING$ FOR SUBDIAGONAL BILINEAR TIME SERIES

  • Lee Oe-Sook
    • Journal of the Korean Statistical Society
    • /
    • 제35권1호
    • /
    • pp.79-90
    • /
    • 2006
  • We consider the subdiagonal bilinear model and ARMA model with subdiagonal bilinear errors. Sufficient conditions for geometric ergodicity of associated Markov chains are derived by using results on generalized random coefficient autoregressive models and then strict stationarity and ,a-mixing property with exponential decay rates for given processes are obtained.

Investigation on Image Quality of Smartphone Cameras as Compared with a DSLR Camera by Using Target Image Edges

  • Seo, Suyoung
    • 대한원격탐사학회지
    • /
    • 제32권1호
    • /
    • pp.49-60
    • /
    • 2016
  • This paper presents a set of methods to evaluate the image quality of smartphone cameras as compared with that of a DSLR camera. In recent years, smartphone cameras have been used broadly for many purposes. As the performance of smartphone cameras has been enhanced considerably, they can be considered to be used for precise mapping instead of metric cameras. To evaluate the possibility, we tested the quality of one DSLR camera and 3 smartphone cameras. In the first step, we compare the amount of lens distortions inherent in each camera using camera calibration sheet images. Then, we acquired target sheet images, extracted reference lines from them and evaluated the geometric quality of smartphone cameras based on the amount of errors occurring in fitting a straight line to observed points. In addition, we present a method to evaluate the radiometric quality of the images taken by each camera based on planar fitting errors. Also, we propose a method to quantify the geometric quality of the selected camera using edge displacements observed in target sheet images. The experimental results show that the geometric and radiometric qualities of smartphone cameras are comparable to those of a DSLR camera except lens distortion parameters.

측량 데이터를 이용한 현수교의 형상오차 원인 추정 (Estimation of Geometric Error Sources of Suspension Bridge using Survey Data)

  • 박용명;조현준;정진환;김남식
    • 한국강구조학회 논문집
    • /
    • 제19권3호
    • /
    • pp.313-321
    • /
    • 2007
  • 본 연구에서는 공용 중인 현수교에서 측량된 데이터를 이용하여 현수교의 형상오차 원인을 추정하는 방법을 제시하였다. 주케이블의 여러 점에서 측량된 데이터와 설계시의 형상과의 차이를 형상오차로 정의하고, 현수교의 형상오차 원인으로 보강형 자중의 변동과 지반의 크리프로 인한 앵커리지 기초의 변형으로 가정하였다. 보강형 자중의 변동 및 앵커리지 기초의 변형에 대한 현수교 구조계의 영향행렬을 이용하여 주케이블의 형상오차를 유발한 자중의 변동량 및 기초의 변형량을 추정하였다. 공용 중인 광안대교를 대상으로 본 기법의 타당성을 검토한 후 실제 측량 데이터를 이용하여 동 교량의 형상오차 원인 분석에 적용하였다.

다축공작기계의 공간오차 예측 및 검증 (Estimation and Evaluation of Volumetric Position Errors for Multi-axis Machine Tools)

  • 황주호;류엔카오;부이바친;박천홍
    • 한국생산제조학회지
    • /
    • 제23권1호
    • /
    • pp.1-6
    • /
    • 2014
  • This paper describes a method of estimating and evaluating the volumetric errors of multi-axis machine tools. The estimation method is based on a generic model that was developed from conventional kinematic error models for the geometric and thermal errors to help predict the volumetric error easily in various configurations. To demonstrate the advantages of the model, an application in the early stages of a five-axis machine tool design is presented as an example. The model was experimentally evaluated for a four-axis machine tool by using the data from ISO230-6 and R-test measurements to compare the estimated and measured volumetric errors.

Geometric charts with bootstrap-based control limits using the Bayes estimator

  • Kim, Minji;Lee, Jaeheon
    • Communications for Statistical Applications and Methods
    • /
    • 제27권1호
    • /
    • pp.65-77
    • /
    • 2020
  • Geometric charts are effective in monitoring the fraction nonconforming in high-quality processes. The in-control fraction nonconforming is unknown in most actual processes; therefore, it should be estimated using the Phase I sample. However, if the Phase I sample size is small the practitioner may not achieve the desired in-control performance because estimation errors can occur when the parameters are estimated. Therefore, in this paper, we adjust the control limits of geometric charts with the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of geometric charts by controlling the probability that the in-control average run length has a value greater than the desired one. The out-of-control performance of geometric charts with adjusted limits is also discussed.