• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1615-1620
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• 2003

Kinematic calibration is a process whereby the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. Measuring all components of Cartesian posture, particularly the orientation, can be difficult. With partial pose measurements, all parameters may not be identifiable. This paper proposes a new device that can identify all kinematic parameters with partial pose measurements. Study is performed for a six degree-of-freedom fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector's motion to five degree-of-freedom and can measure position of the end-effector and one of its rotations. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise. Intrinsic inaccuracies of the device can significantly deteriorate the calibration results. A measurement procedure is proposed and formulations of cost functions are discussed to prevent propagation of the inaccuracies to the calibration results.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1476-1481
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• 2003

Kinematic calibration enhances absolute accuracy by compensating for the fabrication tolerances and installation errors. Effectiveness of calibration procedures depends greatly on the measurements performed. This paper investigates identifiable parameters and optimum postures for four different calibration procedures - measuring postures completely with inverse kinematic residuals, measuring postures completely with forward kinematics residuals, measuring only the three position components, and restraining the mobility of the end-effector using a constraint link. The study is performed for a six degree-of-freedom fully parallel HexaSlide type parallel manipulator, HSM. Results verify that all parameters are identifiable with complete posture measurements. For the case of position measurements, one and for the case of constraint link, three parameters were found non-identifiable. Selecting postures for measurement is also an important issue for efficient calibration procedure. Typically, the condition number of the identification Jacobian is minimized to find optimum postures. Optimal postures showed the same trend of orienting themselves on the boundaries of the search space.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.615-623
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• 2006

The gyroscope free strap-down INS is composed only of accelerometers. Any gyroscope free INS navigation error is deeply affected by the accuracy of the sensor bias, scale factor, orientation and location error. However these parameters can be found by calibration. There is an important research issue about a multi-position calibration method in this paper. It provides a novel method to find the error parameters for the six-accelerometer INS. A superior simulation is shown that the multi-position calibration can find the specifications of a six-accelerometer INS in laboratory. From these parameters the six-accelerometer INS could apply in realistic navigation.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.103-118
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• 2012

A distributed model can easily obtain discharge at any grids spatially distributed in a watershed. But if there are subwatersheds which have various characteristics in a watershed, it is needed to apply a model calibrated at each subwatershed to obtain reliable simulation results for each subwatershed. In this study, a multi-site calibration module that can calibrate a distributed model at each subwatershed using observed flow data was developed. Methods to select multi-site calibration parameters, to apply subwatershed parameters, and to set subwatershed network information are suggested. Classes to implement multi-site calibration technique are designed and a GUI was developed, and procedures for runoff modelling using subwatershed parameters were established. Multi-site calibration module was applied to Sunsan watershed($977km^2$) of Nakdong river basin. Application results showed that the multi-site calibration technique could be applied effectively to model the calibration for each subwatershed, and the simulation results of subwatershed were improved by the application of multi-site calibration.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.802-809
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• 2010

An automatic calibration tool of Hydrological Simulation Program-Fortran (HSPF), Parameter Estimation (PEST) program, was applied at the Imha lake watershed to get optimal hydrological parameters of HSPF. Calibration of HSPF parameters was performed during 2004 ~ 2008 by PEST and validation was carried out to examine the model's ability by using another data set of 1999 ~ 2003. The calibrated HSPF parameters had tendencies to minimize water loss to soil layer by infiltration and deep percolation and to atmosphere by evapotranspiration and maximize runoff rate. The results of calibration indicated that the PEST program could calibrate the hydrological parameters of HSPF with showing 0.83 and 0.97 Nash-Sutcliffe coefficient (NS) for daily and monthly stream flow and -3% of relative error for yearly stream flow. The validation results also represented high model efficiency with showing 0.88 and 0.95, -10% relative error for daily, monthly, and yearly stream flow. These statistical values of daily, monthly, and yearly stream flow for calibration and validation show a 'very good' agreement between observed and simulated values. Overall, the PEST program was useful for automatic calibration of HSPF, and reduced numerous time and effort for model calibration, and improved model setup.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.677-690
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• 2006

The LH-OAT (Latin Hypercube One factor At a Time) method for sensitivity analysis and SCE-UA (Shuffled Complex Evolution at University of Arizona) optimization method were applied for the automatic calibration of SWAT model in Bocheong-cheon watershed. The LH-OAT method which combines the advantages of global and local sensitivity analysis effectively identified the sensitivity ranking for the parameters of SWAT model over feasible parameter space. Use of this information allows us to select the calibrated parameters for the automatic calibration process. The performance of the automatic calibration of SWAT model using SCE-UA method depends on the length of calibration period, the number of calibrated parameters, and the selection of statistical error criteria. The performance of SWAT model in terms of RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), and NMSE (Normalized Mean Square Error) becomes better as the calibration period and the number of parameters defined in the automatic calibration process increase. However, NAE (Normalized Average Error) and SDR (Standard Deviation Ratio) were not improved although the calibration period and the number of calibrated parameters are increased. The result suggests that there are complex interactions among the calibration data, the calibrated parameters, and the model error criteria and a need for further study to understand these complex interactions at various representative watersheds.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.569-574
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• 2003

Computer vision system is broadly adapted like as autonomous vehicle system, product line inspection, etc., because it has merits which can deal with environment flexibly. However, for applying it for that industry, it has to clear the problem that recognize position parameter of itself. So that computer vision system stands in need of camera calibration to solve that. Camera calibration consists of the intrinsic parameter which describe electrical and optical characteristics and the extrinsic parameter which express the pose and the position of camera. And these parameters have to be reorganized as the environment changes. In traditional methods, however, camera calibration was achieved at off-line condition so that estimation of parameters is in need again. In this paper, we propose a method to the calibration of camera using line correspondence in image sequence varied environment. This method complements the corresponding errors of the point corresponding method statistically by the extraction of line. The line corresponding method is strong by varying environment. Experimental results show that the error of parameter estimated is within 1% and those is effective.

• Journal of Internet Computing and Services
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• v.6 no.5
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• pp.57-71
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• 2005

Precise visual measurement applications, like video measuring system (VMS), use camera systems with motorized zoom lens for fast and efficient measurement. In this paper, we introduce an efficient calibration method for zoom lens of VMS controlled by servo motor. For the automated zoom lens calibration of the VMS, only zoom lens setting needs to be calibrated and parameters calibrated by zoom lens settings are image center and pixel size changed by zoom levels, The extrinsic parameters, like focus and iris, do not need to be calibrated since the parameters are usually fixed, It needs a lot of time and effort to calibrate the camera for ali the different zoom levels. In this paper, we also propose an efficient and fast zoom lens calibration method, which calculates the calibration parameters of the zoom lens settings for the minimum number of zoom levels and estimates other parameters for the uncalculated zoom levels using the interpolation of the calculated parameter values.