• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.6 s.237
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• pp.795-803
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• 2005

This paper studies the observability of calibration system with a measurement operator. The calibration system needs a simple digital indicator to measure the mobile table movements with respect to the MC coordinate. However, it yields the concern about the poor parameter observability due to measuring only a part of the movements. We uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of an observation matrix. The number of identifiable parameter is examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a 6-axis MC with parallel tilting table and the calibration results are presented. These results verify that all necessary kinematic parameters are observable and the calibration system has robustness to the noise using optimal calibration configurations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.647-655
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• 2003

This paper studies the observability of calibration system with a constraint movement by a constraint operator. The calibration system with the constraint movement need only simple sensing device to check whether the constraint movements are completed within an established range. However, it yields the concern about the poor parameter observability due to the constraint movements. This paper uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of a observation matrix. The number of identifiable parameters are examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a parallel typed machining center and the calibration results are presented. These results verify that the calibration system with low-cost indicators and simple planar table is accurate as well as reliable.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1512-1517
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• 2003

This paper presents the calibration for the parallel typed tilting table. The calibration system needs only simple sensing device which is a digital indicator to measure the orientation of a table. The calibration algorithm is developed by a measurement operator. It eliminates the concern about the poor parameter observability due to a large number of parameters of parallel-mechanism. This paper uses the QR-decomposition to find the optimal calibration configurations maximizing the linear independence of rows of a observation matrix. The number of identifiable parameters is examined by the rank of the observation matrix, which represents the parameter observability. The method is applied to a Parallel-typed Tilting Table and all the necessary kinematic parameters are identifiable.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.746-752
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• 2014

In a multi-camera measurement system, the determination of the external parameters is one of the vital tasks, referred to as the calibration of the system. In this paper, a new geometrical calibration method, which is based on the theory of the vanishing line, is proposed. Using a planar target with three equally spaced parallel lines, the normal vector of the target plane can be confirmed easily in every camera coordinate system of the measurement system. By moving the target into more than two different positions, the rotation matrix can be determined from related theory, i.e., the expression of the same vector in different coordinate systems. Moreover, the translation matrix can be derived from the known distance between the adjacent parallel lines. In this paper, the main factors effecting the calibration are analyzed. Simulations show that the proposed method achieves robustness and accuracy. Experimental results show that the calibration can reach 1.25 mm with the range about 0.5m. Furthermore, this calibration method also can be used for auto-calibration of the multi-camera mefasurement system as the feature of parallels exists widely.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1886-1893
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• 2003

This paper examines the parameter observability of a calibration system that consrains a mobile platform to a planar table to take the calibration data. To improve the parameter observability, we find the optimal configurations providing the calibration with maximum contribution. The QR-decomposition is used to compute the optimal configurations that maximize the linear independence of rows of an observation matrix. The calibration system is applied to the parallel type manipulator constructed for a machining center. The calibration results show that all the necessary kinematic parameters assigned in a Stewart-Gough platform are identifiable and convergent to desirable accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.491-499
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• 2018

The conventional calibration method for a noise figure analyzer is to use a noise source. This method is accompanied by a significant irregular ripple in the measurement results, because it does not consider the mismatch of the noise source and noise figure analyzer during calibration. A novel calibration method of the noise figure analyzer is proposed that considers the mismatch between the noise power and noise figure analyzer. A novel noise correlation matrix measurement technique using this method is also proposed. The method determines the noise correlation matrix and the gain of the uncorrected noise figure analyzer using uncorrected noise powers. Then, having determined the gain and noise correlation matrix, the effects of noise figure analyzers were corrected in the measurement results of the noise correlation matrix for the device under test (DUT). Through the proposed method, the measured noise parameters of a DUT showed the same degree of irregular ripples as the result of using the relative noise ratio.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.38-46
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• 2008

Key-frame selection algorithm is defined as the process of selecting a necessary images for 3D reconstruction from the uncalibrated images. Also, camera calibration of images is necessary for 3D reconstuction. In this paper, we propose a new method of Key-frame selection with the minimal error for camera calibration. Using the full-auto-calibration, we estimate camera parameters for all selected Key-frames. We remove the false matching using the fundamental matrix computed by algebraic deviation from the estimated camera parameters. Finally we obtain 3D reconstructed data. Our experimental results show that the proposed approach is required rather lower time costs than others, the error of reconstructed data is the smallest. The elapsed time for estimating the fundamental matrix is very fast and the error of estimated fundamental matrix is similar to others.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.387-393
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• 2004

General purpose of cylindrical capacitive displacement sensor(CCS) is measuring run-out motion and deflection of rotor. If CCS has narrow sensing range, its sensitivity coefficients must be calibrated precisely. And x, y component of CCS output can be coupled. In this research, CCS calibration procedure is automated with automatic calibration program and PC-controlled stage. And, coupled-terms of CCS signals were removed and the errors between measured position and mapped CCS signal were reduced obviously by sensitivity matrix that linearly.

• Mass Spectrometry Letters
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• v.9 no.3
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• pp.77-80
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• 2018

The focus of this paper is to present techniques to overcome certain difficulties in quantitative analysis with a time-of-flight mass spectrometer (TOF-MS). The method is based on conventional solid-phase extraction, followed by reversed-phase ultra high performance liquid chromatography of the extract, and mass spectrometric analysis. The target compounds included atenolol, atrazine, caffeine, carbamazepine, diclofenac, estrone, ibuprofen, naproxen, simazine, sucralose, sulfamethoxazole, and triclosan. The matrix effects caused by high concentrations of organic compounds in wastewater are especially significant in electrospray ionization mass spectroscopy. Internal-standard calibration with isotopically labeled standards corrects the results for many matrix effects, but some peculiarities were observed. The problems encountered in quantitation of carbamazepine and triclosan, due to nonlinear calibration were solved by changing the internal standard and using a narrower mass window. With simazine, the use of a quadratic calibration curve was the best solution.