• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.513-518
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• 1987

In this paper the error equations of the SDINS aligned by the gyrocompass are derived considering that the alignment errors are correlated to the sensor errors. Also the navigation errors due to the correlated errors are simulated by this error equations. The simulations are performed by the covariance analysis method, assumed all the sensor errors are random constants. The simulation results show that while the INS maintains the alignment attitude the cancellation takes place between the correlated errors, but once the INS changes attitude this cancellation effect is perturbed.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.665-671
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• 1994

Some extended results in the study of two-position alignment for strapdown inertial navigation system are presented. In [1], an observability analysis for two-position alignment was done by analytic rank test of the stripped observability matrix and numerical calculation of the error covariance propagation using ten-state error model. In this paper, it is done by an analytic approach which utilizes the nonsingular condition of the determinant of simplified stripped observability matrix and by numerical calculation of the error covariance propagation accomplished in more cases than [1], and the twelve-state error model including vertical channel is used instead of ten-state error model. In addition, it is confirmed that this approach more clearly produces the same result as shown in the original work in terms of complete observability and there exist some better two-position configurations than [1] using the twelve-state error model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.463-472
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• 2017

Inertial Navigation System Alignment is the process to determine direction cosine matrix which is the transformation matrix between the INS body frame and navigation frame. INS initial position value is necessary to INS attitude calculation, so that user should wait until he get such value to start the INS alignment. To remove the waiting time, we propose an alignment algorithm that immediately starts after the INS power on by using pseudo initial position input and then is completed with attitude error compensation by entering true position later. We analyse effect of INS sensor error on attitude in process of time and verify the performance and usefulness of the close-loop alignment algorithm which corrects attitude error from the change of initial position.

• Transactions of Materials Processing
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• v.32 no.6
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• pp.376-383
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• 2023

The torsion bar, which is a steering torque sensor, is mounted between the steering pinion and the input shaft in the IPA(input pinion assembly). Accurate torque measurement is important to improve the sense of operation, and the straightness of the torsion bar can affect torque measurement. In this study, the amount of bending was measured and the exact shape was analyzed regarding the bending phenomenon in the press-fitting process for torsion bars. The effect of alignment error was analyzed through finite element forming analysis. Process data analysis was conducted for the double-end press fit model. If there is an alignment error of about 10% of the serration tooth height, the indentation load is reduced by about 10%. If there is an alignment error, the torsion bar is rotated.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.96-104
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• 2003

This paper presents the measurement and correction method of PCB alignment errors for PCB screen printer. Electronic equipment is getting smaller and yet must satisfy high performance standard. Therefore, there is a great demand for PCB with high density. However conventional PCB screen printer doesn't have enough accuracy to accommodate the demand for high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because the alignment errors of PCB occur when it is loaded to the screen printer. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors with high-accuracy. An automatic optical inspection part measures the PCB alignment errors using machine vision, and the high-accuracy 3-axis stage makes correction for these errors. This system used two CCD cameras to get images of two fiducial marks of PCB. The centers of fiducial marks are obtained by using moment, gradient method. The first method is calculating the centroid by using first moment of blob, and the latter method is calculating the center of the circle whose equation is obtained by curve-fitting the boundaries of fiducial mark. The operating system used to implement the whole set-up is carried in Window 98 (or NT) environment. Finally we implemented this system to PCB screen printer.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.6
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• pp.607-614
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• 2013

In this study, effect of the sensor gain error is theoretically analyzed and simulated when mixed sequential two-prove method(MTPM) is applied for the precision measurement of straightness error of a linear motion table. According to the theoretical analysis, difference of the gain errors between two displacement sensors increases measurement error dramatically and alignment error of the straightedge is also amplified by the sensor gain difference. On the other hand, if the gain errors of the two sensors are identical, most of error terms are cancelled out and the alignment error doesn't give any influence on the measurement error. Also the measurement error of the straightness error is minimized compared with that of the straightedge's form error owing to close relationship between straightness error and angular motion error of the table in the error terms.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.177.3-177
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• 2001

In this paper, the design of the in-motion alignment system of Strapdown Inertial Navigation System(SDINS) using Robust Extended Kalman Filter(REKF) is presented. The compensation of errors in the aided navigation system is accomplished by the indirect feedback filtering. The performance of the aided navigation algorithm is very sensitive to the accuracy of the initial estimate, which is the characteristic of the EKF. Unfortunately, the initial attitude error can be very large during the in-motion alignment. To overcome the in-motion alignment under large initial attitude error problem, the REKF using linear robust filtering technique is proposed. The linear robust H$_2$ filter can be adopted for nonlinear ...

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.118-126
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• 2014

In this paper, a new method is proposed for the five-degree-of-freedom precision alignment and stitching of three-dimensional surface-profile data sets. The control parameters for correcting thealignment error are calculated from the surface profile data for overlapped areas among the adjacent measuring areas by using the "least squares method" and "maximum lag position of cross correlation function." To ensure the alignment and stitching reliability, the relationships betweenthe alignment uncertainty, overlapped area, and signal-to-noise level of the measured profile data are investigated. Based on the results of this uncertainty analysis, an appropriate size is proposed for the overlapped area according to the specimen's surface texture and noise level.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.686-692
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• 2016

A Crimp Force Monitor (CFM) is equipment for detecting crimp errors by analyzing crimp signals obtained from force and strain sensors. The analysis is commonly performed by aligning a measured crimp signal with a reference signal and comparing their difference. Current analysis methods often suffer from wrong alignments that result in false negative detections. This paper presents a new crimp signal analysis method in CFM. First, a falling edge alignment is proposed that matches falling edges of the measured and the reference signals by minimizing the absolute difference summation. Second, a signal parameter error is introduced to evaluate the crimp quality difference between the measured signal and the reference. For calculating the signal parameter error, part of a signal is identified and divided into several regions to maximize the signal parameter errors. Experiments showed that the proposed method can improve the signal alignment and accurately detect bad crimps especially with the strain sensor.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.379-385
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• 2024

INS(inertial navigation system) aligns itself using gravity and Earth's rotational rate from accelerometers and gyro sensors when stationary. Typically, ZUPT(zero velocity update), which is based on a linear error model Kalman filter, is used when it is stationary. However, such algorithms assume stationary conditions, leading to increased alignment errors or filter divergence during maritime mooring due to wave-induced motion. This paper designs a mooring alignment algorithm for maritime platforms using a Kalman filter, which uses large heading angle error model and an initial position correction technique. And it is validated by simulation. Furthermore, it is confirmed that applying this to a rotational INS dramatically improves performance through the principle of bias cancellation.