• Title/Summary/Keyword: Calibration Map

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Full angle range pressure coefficient maps of five-hole probe and new calibration coefficients (5공프로브의 전 각도 범위 압력계수 지도와 새로운 보정계수)

  • Kim, Jin-Gwon;Gang, Sin-Hyeong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.21 no.11
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    • pp.1437-1448
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    • 1997
  • Pressures of a five-hole probe were measured for a full range of yaw and pitch angles and complete pressure coefficient maps were obtained. Based on these maps, various features of five-hole probe pressures were revealed and new five-hole probe calibration coefficients were devised. The new calibration coefficients show non-diverging characteristics for any flow direction and one-to-one correspondence for a wide range of flow angles. These calibration coefficients expand the valid flow angle range of five-hole probe calibration by .+-.10 degrees and complement a critical defect of five-hole probe zone-division calibration method which has not been known yet. Moreover new non-diverging calibration coefficients have advantages in nulling methods, too.

Vector Calibration for Geomagnetic Field Based Indoor Localization (지자기 기반 실내 위치 추정을 위한 지자기 벡터 보정법)

  • Son, Won Joon;Choi, Lynn
    • The Journal of Korean Institute of Next Generation Computing
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    • v.15 no.3
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    • pp.25-30
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    • 2019
  • Magnetic sensors have the disadvantage that their vector values differ depending on the direction. In this paper, we propose a magnetic vector calibration method for geomagnetic-based indoor localization estimates. The fingerprinting technique used in geomagnetic-based indoor localization the position by matching the magnetic field map and the magnetic sensor value. However, since the moving direction of the current user may be different from the moving direction of the person who creates the magnetic field map at the collection time, the sampled magnetic vector may have different values from the vector values recorded in the field map. This may substantially lower the positioning accuracy. To avoid this problem, the existing studies use only the magnitude of magnetic vector, but this reduces the uniqueness of the fingerprint, which may also degrade the positioning accuracy. In this paper we propose a vector calibration algorithm which can adjust the sampled magnetic vector values to the vector direction of the magnetic field map by using the parametric equation of a circle. This can minimize the inaccuracy caused by the direction mismatch.

Evaluation of Applicability of SWAT-CUP Program for Hydrologic Parameter Calibration in Hardware Watershed (Hardware 유역의 수문매개변수 보정을 위한 SWAT-CUP 프로그램의 적용성 평가)

  • Sang Min, Kim
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.3
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    • pp.63-70
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    • 2017
  • The purpose of this study was to calibrate the hydrologic parameters of SWAT model and analyze the daily runoff for the study watershed using SWAT-CUP. The Hardware watershed is located in Virginia, USA. The watershed area is $356.15km^2$, and the land use accounts for 73.4 % of forest and 23.2 % of pasture. Input data for the SWAT model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1990 to 1994 was used for calibration and from 1997 to 2005 was for validation. The SUFI-2 module of the SWAT-CUP program was used to calibrate the hydrologic parameters. The parameters were calibrated for the highly sensitive parameters presented in previous studies. The P-factor, R-factor, $R^2$, Nash-Sutcliffe efficiency (NS), and average flow were used for the goodness-of-fit measures. The applicability of the model was evaluated by sequentially increasing the number of applied parameters from 4 to 11. In this study, 10-parameter set was accepted for calibration in consideration of goodness-of-fit measures. For the calibration period, P-factor was 0.85, R-factor was 1.76, $R^2$ was 0.51 and NS was 0.49. The model was validated using the adjusted ranges of selected parameters. For the validation period, P-factor was 0.78, R-factor was 1.60, $R^2$ was 0.60 and NS was 0.57.

Calibration/Compensation of Errors of the Touch Probe (접촉식 프로브의 오차교정 및 보정기술)

  • 박희재;이교일
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.8
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    • pp.2081-2087
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    • 1994
  • Touch trigger probes are widely used for inspection purposed in the CMM(Coordinate meauring machine) or machine tool. The errors introduced by measurement probe are fairy systematic, thus can be calibrated and compensated properly. This paper presents a technique for the error calibration and compensation of the probe errors, which can be easily applicable to the manufacturers and users of the measurement probe. The probe coordinate system is defined for the probe error assessment, and a reference sphere ball is measured, and the probe errors are calibrated. The calibrated probe errors are represented in the 3D error map and 2D error map along probing direction. Detail algorithms for the error compensation are proposed.

Measurement System Development for Three-Dimensional Flow Velocity Components Using Straight-Type Five-Hole Pressure Probe (직선형 5공 압력프로브를 이용한 3차원 유동속도 계측시스템 개발)

  • Kim, J.K.;Jeong, K.J.;Oh, S.H.
    • Journal of Power System Engineering
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    • v.10 no.4
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    • pp.56-64
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    • 2006
  • This paper shows the development process of a straight-type five-hole pressure probe for measuring three-dimensional flow velocity components. The data reduction method using a bi-cubic curve-fitting program in a new calibration map was introduced in this study. This new calibration map can be applied up to the application angle, ${\pm}55^{\circ}$ of a probe. As a result, for the application angle of ${\pm}45^{\circ}$, an error for yaw and pitch angles appeared from $-1.76^{\circ}\;to\;1.83^{\circ}$ and from $-1.91^{\circ}\;to\;1.75^{\circ}$, respectively. Moreover, an error for a vector magnitude and a static pressure compared with a dynamic one showed from -7.83% to 4.87% and from -0.73 to 0.77, respectively. Even though this data reduction method showed unsatisfactory errors in a vector magnitude, it resulted in an easy and simple application method. Especially, when it was applied to an actual flow field including a swirling flow, a good result came out on the whole. However, in order to obtain a better result, it is thought that a more sophisticated interpolation method needs to be introduced.

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Neural Network Based Camera Calibration and 2-D Range Finding (신경회로망을 이용한 카메라 교정과 2차원 거리 측정에 관한 연구)

  • 정우태;고국원;조형석
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.510-514
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    • 1994
  • This paper deals with an application of neural network to camera calibration with wide angle lens and 2-D range finding. Wide angle lens has an advantage of having wide view angles for mobile environment recognition ans robot eye in hand system. But, it has severe radial distortion. Multilayer neural network is used for the calibration of the camera considering lens distortion, and is trained it by error back-propagation method. MLP can map between camera image plane and plane the made by structured light. In experiments, Calibration of camers was executed with calibration chart which was printed by using laser printer with 300 d.p.i. resolution. High distortion lens, COSMICAR 4.2mm, was used to see whether the neural network could effectively calibrate camera distortion. 2-D range of several objects well be measured with laser range finding system composed of camera, frame grabber and laser structured light. The performance of 3-D range finding system was evaluated through experiments and analysis of the results.

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A Robust Depth Map Upsampling Against Camera Calibration Errors (카메라 보정 오류에 강건한 깊이맵 업샘플링 기술)

  • Kim, Jae-Kwang;Lee, Jae-Ho;Kim, Chang-Ick
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.6
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    • pp.8-17
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    • 2011
  • Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

Underwater Magnetic Field Mapping Using an Autonomous Surface Vehicle (자율수상선을 이용한 수중 자기장 지도 작성)

  • Jung, Jongdae;Park, Jeonghong;Choi, Jinwoo
    • The Journal of Korea Robotics Society
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    • v.13 no.3
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    • pp.190-197
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    • 2018
  • Geomagnetic field signals have potential for use in underwater navigation and geophysical surveys. To map underwater geomagnetic fields, we propose a method that exploits an autonomous surface vehicle. In our system, a magnetometer is rigidly attached to the vehicle and not towed by a cable, minimizing the system's size and complexity but requiring a dedicated calibration procedure due to magnetic distortion caused by the vehicle. Conventional 2D methods can be employed for the calibration by assuming the horizontal movement of the magnetometer, whereas the proposed 3D approach can correct for horizontal misalignment of the sensor. Our method does not require a supporting crane system to rotate the vehicle, and calibrates and maps simultaneously by exploiting data obtained from field operation. The proposed method has been verified experimentally in inland waters, generating a magnetic field map of the test area that is of much higher resolution than the public magnetic field data.

Quantitative analysis method for zingiber officinale water extract using high-performance liquid chromatography

  • Mohd S. Md Sarip;Nik M.A. Nik Daud;Mohd A. Mohd Zainudin;Lokman H. Ibrahim;Syahrul A. Saidi;Zuhaili Idham;Adilah Anuar
    • Advances in materials Research
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    • v.13 no.3
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    • pp.233-241
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    • 2024
  • Quantitative analysis of the Zingiber Officinale sample using subcritical water extraction (SWE) was developed employing High-Performance Liquid Chromatography (HPLC) to bolster the advancement of this innovative green extraction process. This research focuses on three principal ginger bioactive compounds: 6-gingerol, 6-shagoal, and 10-gingerol. Various stages were undertaken to establish the quantitative analysis method, encompassing the optimisation of HPLC operating conditions and the formulation of standard calibration curves, yielding individual compound equations. A robust correlation within the calibration curve was achieved, exhibiting an r2 value of 0.9814 and an RSD of 5.00%. A simultaneous, swift, and dependable method was established with an injection time of 20 minutes and an 8-minute delay between injections, in contrast to the previous HPLC analysis requiring a 45-minute injection time for detecting and quantifying all components. Notably, no post-treatment was applied after the SWE process. This advancement allows for potential future online measurement of Zingiber Officinale bioactive compounds extracted using subcritical water extraction through this technology.

Segmentation-Based Depth Map Adjustment for Improved Grasping Pose Detection (물체 파지점 검출 향상을 위한 분할 기반 깊이 지도 조정)

  • Hyunsoo Shin;Muhammad Raheel Afzal;Sungon Lee
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.16-22
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    • 2024
  • Robotic grasping in unstructured environments poses a significant challenge, demanding precise estimation of gripping positions for diverse and unknown objects. Generative Grasping Convolution Neural Network (GG-CNN) can estimate the position and direction that can be gripped by a robot gripper for an unknown object based on a three-dimensional depth map. Since GG-CNN uses only a depth map as an input, the precision of the depth map is the most critical factor affecting the result. To address the challenge of depth map precision, we integrate the Segment Anything Model renowned for its robust zero-shot performance across various segmentation tasks. We adjust the components corresponding to the segmented areas in the depth map aligned through external calibration. The proposed method was validated on the Cornell dataset and SurgicalKit dataset. Quantitative analysis compared to existing methods showed a 49.8% improvement with the dataset including surgical instruments. The results highlight the practical importance of our approach, especially in scenarios involving thin and metallic objects.