• Title/Summary/Keyword: 각도 보정

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Evaluation of the Inherent Flow Coefficient of the Control Valve in the Liquid Propellant Rocket Engine (액체로켓 엔진 성능 보정용 제어밸브의 고유유량특성 계산)

  • Park, Soon-Young;Cho, Won-Kook;Seol, Woo-Seok
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2010.11a
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    • pp.585-589
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    • 2010
  • It is important for the liquid rocket engine to meet the exact performance requirements in order to guarantee the successful mission of the launch vehicle. Usually, a ground combustion test for the engine is conducted to reduce the performance error and for the tuning. For the gas-generator (GG) cycle engine, this adjustment process can be easily tuned by means of the control valves. A linearized correlation between the process parameters of the control - the combustion chamber pressure and the mixture ratio of engine - and the independent parameter of the control- rotational angle of the control valve - could be suitable to reduce the tuning errors. Also this linearity can reduce the effort for the tuning and make the process more explicit by ensuring a more intuitive control. In this point, we proposed an algorithm in the frame of the in-house-developed program to obtain the control valves' inherent characteristics which satisfy the linearity.

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A study on the imputation solution for missing speed data on UTIS by using adaptive k-NN algorithm (적응형 k-NN 기법을 이용한 UTIS 속도정보 결측값 보정처리에 관한 연구)

  • Kim, Eun-Jeong;Bae, Gwang-Soo;Ahn, Gye-Hyeong;Ki, Yong-Kul;Ahn, Yong-Ju
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.13 no.3
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    • pp.66-77
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    • 2014
  • UTIS(Urban Traffic Information System) directly collects link travel time in urban area by using probe vehicles. Therefore it can estimate more accurate link travel speed compared to other traffic detection systems. However, UTIS includes some missing data caused by the lack of probe vehicles and RSEs on road network, system failures, and other factors. In this study, we suggest a new model, based on k-NN algorithm, for imputing missing data to provide more accurate travel time information. New imputation model is an adaptive k-NN which can flexibly adjust the number of nearest neighbors(NN) depending on the distribution of candidate objects. The evaluation result indicates that the new model successfully imputed missing speed data and significantly reduced the imputation error as compared with other models(ARIMA and etc). We have a plan to use the new imputation model improving traffic information service by applying UTIS Central Traffic Information Center.

A Comparison of Correction Models for the Prediction of Tropospheric Propagation Delay of GPS Signals (GPS 신호의 대류층 지연 예측을 위한 보정모델의 비교)

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    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.20 no.3
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    • pp.283-291
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    • 2002
  • Since GPS's SA cancellation, the interest is converged in correction of errors such as atmospheric delay and multipath that weight had been small relatively, which can improve the accuracy of positioning through modelling research. The aim of this study have an extensive comparison of the various tropospheric delay models (Goad&Goodman, A&K, Hopfield and Sasstamoinen) and mapping functions(Niell, Chao, and Marini). Expecially, the tropospheric delay amounts by change of the GPS satellite elevations, and the delay by various combination between zenith delay models and mapping functions, compared and examined. For this, programmed the total delay models and the combined models which can be described as a product of the delay at the zenith and a mapping function. The result of study, especially, as the minimum elevation of included data is reduced under $10^{\circ}$, it was considered to be reasonable that the prediction of tropospheric delay considering combination and mapping character of functions about the transition of the zenith delay to a delay with arbitrary zenith angle.

An Adaptive Pointing and Correction Algorithm Using the Genetic Algorithm (유전자 알고리즘을 이용한 적응적 포인팅 및 보정 알고리즘)

  • Jo, Jung-Jae;Kim, Young-Chul
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.67-74
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    • 2013
  • In this paper, we propose the pointing and correction algorithm for optimized performance based on Bluetooth communication. The error from the accelerometer sensor's output must be carefully managed as the accelerometer sensor is more sensitive to data change compared to that of the gyroscope sensor. Thus, we minimize the noise by applying the Kalman filter to data for each axis from the accelerometer. In addition, we can also obtain effect compensating the hand tremor by applying the Kalman filter to the data variation for x and y. In this study, we extract data through the Quaternion mapping process on data from the accelerometer and gyroscope. In turn, we can obtain a tilt compensation by applying a compensation algorithm with acceleration of the gravity of the extracted data. Moreover, in order to correct the inaccuracy on smart sensor due to the rapid movement of a device, we propose a adaptive pointing and correction algorithm using the genetic approach to generate the initial population depending on the user.

Evaluate the usefulness of Coincidence Summing Correction Factors for Cylinder and Extended Source Penelope Simulation (실린더 및 확장 소스 PENELOPE 시뮬레이션에 대한 동시합성보정 계수 유용성 평가)

  • Jang, Eun-Sung;Chang, Bo-Seok
    • Journal of the Korean Society of Radiology
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    • v.15 no.6
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    • pp.821-831
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    • 2021
  • In order to calibrate energy and efficiency using the PENELOPE Code, a PENELOPE simulation was performed using a volume source. Here, we want to verify peak efficiency and usefulness by performing simultaneous measurement and correction. calculate the coincident sum correction for all volumes, first subdivide the volumes of the cylinder and the four Marinelli beakers into three heights again. Therefore, the simultaneous measurement correction coefficient in three areas and the simultaneous measurement correction coefficient for the entire volume source are calculated as output. At low energies, the j value for each source volume (50-300 ml) is small and increases significantly in the high energy range. Simulation results showed good agreement within 2.5% for all source volumes except for 50 ml and 300 ml, which were up to 4%. This means that the correction for the simultaneous measurement effect during measurement is effective. In addition. Based on this, it can be confirmed that there is an advantage to improve the detection efficiency when measuring various sources and environmental samples.

Calibration of VLP-16 Lidar Sensor and Vision Cameras Using the Center Coordinates of a Spherical Object (구형물체의 중심좌표를 이용한 VLP-16 라이다 센서와 비전 카메라 사이의 보정)

  • Lee, Ju-Hwan;Lee, Geun-Mo;Park, Soon-Yong
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.2
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    • pp.89-96
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    • 2019
  • 360 degree 3-dimensional lidar sensors and vision cameras are commonly used in the development of autonomous driving techniques for automobile, drone, etc. By the way, existing calibration techniques for obtaining th e external transformation of the lidar and the camera sensors have disadvantages in that special calibration objects are used or the object size is too large. In this paper, we introduce a simple calibration method between two sensors using a spherical object. We calculated the sphere center coordinates using four 3-D points selected by RANSAC of the range data of the sphere. The 2-dimensional coordinates of the object center in the camera image are also detected to calibrate the two sensors. Even when the range data is acquired from various angles, the image of the spherical object always maintains a circular shape. The proposed method results in about 2 pixel reprojection error, and the performance of the proposed technique is analyzed by comparing with the existing methods.

The correction of Lens distortion based on Image division using Artificial Neural Network (영상분할 방법 기반의 인공신경망을 적용한 카메라의 렌즈왜곡 보정)

  • Shin, Ki-Young;Bae, Jang-Han;Mun, Joung-H.
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.4
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    • pp.31-38
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    • 2009
  • Lens distortion is inevitable phenomenon in machine vision system. More and more distortion phenomenon is occurring in order to choice of lens for minimizing cost and system size. As shown above, correction of lens distortion is critical issue. However previous lens correction methods using camera model have problem such as nonlinear property and complicated operation. And recent lens correction methods using neural network also have accuracy and efficiency problem. In this study, I propose new algorithms for correction of lens distortion. Distorted image is divided based on the distortion quantity using k-means. And each divided image region is corrected by using neural network. As a result, the proposed algorithms have better accuracy than previous methods without image division.

Prevention of Collision with Other Vessels Using Camera Sensors with Kalman Filter (칼만 필터가 적용된 카메라 센서를 이용한 타 선박과의 충돌 예방)

  • Dae-il Sung;Sung-Joo Kim;Young-Min Kim;Yun-Sung Jung;Min-Seok Han
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.3
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    • pp.130-140
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    • 2024
  • In this paper, we present a method of applying the kalman filter to control and correct errors in camera sensor recognition depending on the sea state environment. First, the specifications of the ship were described and the degree of error due to rolling was measured. After presenting the distance from the surface of the water to the sidelight required for simulation through PKMR-211, the ship selected as the model, error correction was performed using the camera error value as a variable in the feedback control system. In the experiment, the degree of rolling of the ship was expressed as variables 𝛼 and 𝛽, expressed in angles, and the angle change according to distance was compared. When comparing the error before and after applying the kalman filter in sea state 4, it decreased from +1.5556° to -1.1544° in red light regardless of distance, and the same result was confirmed in green light. Through this, calculations were performed considering the movement of the ship according to the maritime environment, and the future maneuverability of the ship was presented after error correction.

Risk Factors for Malassezia pachydermatis-associated Dermatitis in dogs: a Case-control Study (개에서 Malassezia pachydermatis에 의한 피부염의 위험요인에 관한 Case-control 연구)

  • Son-il Pak;Hwa-young Youn
    • Journal of Veterinary Clinics
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    • v.16 no.1
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    • pp.80-85
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    • 1999
  • Malassezia(Pityrosoprum) pachydermatis에 의한 피부염의 위험요인을 파악하고자 1997년 1월에서 1998년 12월까지 서울대학교 수의과대학 부속동물병원에 내원하여 본 질환으로 진단된 29두와 동일한 기간 동안 피부과 검사에서 임상적으로 건강한 개로 확인된 97 두의 대조군을 대상으로 분석하였다. 각 설명변수에 대한 교차비(odds ratio, OR)와 신뢰구간(confidence interval, CI)은 변수보정법을 사용하여 계산하였다. 다른 공변수를 보정한 상태에서 다중 로지스틱 회귀분석(multiple logistic regression analysis)을 시행한 결과 피부병기왕력(p=0.0059; OR, 4.44; CI, 1.5∼12.8)과 비만(p=0.0013; OR, 5.38; CI, 1.9∼14.9)은 유의한 위험요인으로 나타났다. 단변량 분석(univariate analysis)에서 주 사료로 고기를 섭취하는 경우 피부염의 위험이 높은 변수로 작용하였지만(p=0.0398; OR, 6.38; CI, 1.1∼37.3) 다른 공변수를 보정한 분석에서는 유의하지 않은 것으로 나타났다. 성별, 품종, 및 예방접종은 위험요인으로 작용하지 않았다.

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Development of autonomous driving system using GPS (GPS를 이용한 자율주행 시스템 개발)

  • Oh, Young-Jun;Jung, Keun-Ho;Jeon, Euy-Sik
    • Proceedings of the KAIS Fall Conference
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    • 2009.12a
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    • pp.695-698
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    • 2009
  • 오늘날 네비게이션 시스템이 대부분의 차량에 필수장비가 될 정도로 GPS는 우리도 모르게 많이 사용되고 있고 많은 연구가 진행되어 있다. 그러나 대부분 차량용 네비게이션은 도로의 정보를 통하여 GPS의 불확실한 정보를 보정하게 되지만 도로정보를 참조할 수 없는 해상이나 공중에서 사용하기 위해서는 보정이 어려운 것이 사실이다. 본 논문에서는 이동로봇에 대하여 일반 도로가 아닌 개활지에서의 자율주행을 목표로 한 시스템을 개발하였다. 연구내용으로는 NXT 로봇과 Compass Sensor, 그리고 Bluetooth GPS를 이용하여 도로의 정보가 없이 로봇의 위치를 보정하였고, 목표점까지의 거리와 각도를 계산한 후 자율 주행이 가능하도록 LabView로 프로그래밍 하였다. 결과적으로 NXT 로봇의 목표지점간 최적이동 알고리즘을 구현하였고 실험을 통하여 이를 증명하였다.

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