• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.507-514
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• 2003

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. Recently the shape measurement using interferometric principle is found to be a successful methodology among other visual or optical technologies. Especially, the measuring method using wavelength scanning interferometer(WSI) has a great advantage in comparison with other conventional jnterferometric methods in that the absolute distance from the reference surface can be directly obtained from the amount of jnterferometric phase change. However, the measurement methods using WSI proposed by other researchers have low measurement resolution so far because they can't measure fractional phase change. To avoid this shortcoming we propose a new algorithm in this paper, which can obtain a small amount of even fractional phase change by sinusoidal function fitting. To evaluate the effectiveness of the proposed sinusoidal function fitting algorithm, a series of measuring experiments are conducted for discontinuously shaped specimens which have various height. The proposed algorithm shows much more enhanced measurement resolution than other existing conventional algorithms such as zero crossing algorithm and Fourier transform algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.677-685
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• 2008

This paper proposes algorithm for the obstacle detection and classification using a single laser scanner. In a measurement data from a laser scanner, there exist points with large differential value called singular points, which can be used to obtain the boundary of an obstacle such that obstacle information can be analyzed. On the other hand, measurement data include a lot of measurement error, which makes it difficult to analyze the accurate obstacle information. To solve this problem, the least square estimation algorithm is used to obtain the accurate information using a single laser scanner, by compensation for the measurement error. This algorithm can be used for the effective obstacle avoidance of mobile robots, and the experimental results are included to demonstrate the effectiveness of the propose algorithm.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.71-78
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• 2000

Quickness and precision are the two most important requirements for an industrial scale used in production lines. In this paper, a new approach, "Mass-estimation algorithm by vibration-response measurement of dynamic balance", is presented to improve some of drawbacks in conventional scales. The system, consisted of velocity and displacement sensors, spring scale, analog-digital converter and microcomputer, is based on full utilization of dynamic mass measurement of velocity and displacement via microcomputer-assisted real time monitoring. The resulting system, when combined with appropriate mass estimation algorithm software, has shown its effectiveness in terms of two desirable characteristics required.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.778-790
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• 2023

Although density peak clustering can often easily yield excellent results, there is still room for improvement when dealing with complex, high-dimensional datasets. One of the main limitations of this algorithm is its reliance on geometric distance as the sole similarity measurement. To address this limitation, we draw inspiration from the information bottleneck theory, and propose a novel density peak clustering algorithm that incorporates this theory as a similarity measure. Specifically, our algorithm utilizes the joint probability distribution between data objects and feature information, and employs the loss of mutual information as the measurement standard. This approach not only eliminates the potential for subjective error in selecting similarity method, but also enhances performance on datasets with multiple centers and high dimensionality. To evaluate the effectiveness of our algorithm, we conducted experiments using ten carefully selected datasets and compared the results with three other algorithms. The experimental results demonstrate that our information bottleneck-based density peaks clustering (IBDPC) algorithm consistently achieves high levels of accuracy, highlighting its potential as a valuable tool for data clustering tasks.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.109-116
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• 1994

Quickness and precision are the two most important requirements for an industrial scale used in production lines. In this paper, a new approach, "Dynamic-Mass measurement control System of Acceleration and Displacement(DMS-AD) sensing", is presented to improve some of drowbacks in conventional scales. The system, consisted of acceleration and displace- ment sensors, spring scale and microcomputer, is based on full utilization of dynamic mass measurement of acceleration and displacement via microcomputer-assisted real time monitoring. The rsulting system, when combined with appropriate dynamic mass estimation algorithm software, has shown its effectiveness in terms of two desirable characteristics required. required.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.263-277
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• 2018

This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.71-76
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• 2001

In the surface measurement system using touch probe, probe radius compensation is a key factor for accuracy. In this paper we investigate methods for compensating probe radius so that the surface equation for an "unknown surface" can be efficiently derived. The developed algorithm derives the surface equation by the iterative procedure of estimation, verification, and modification . Since the procedure is applied only for the surface region exceeding the tolerance limit, an accurate surface equation can be obtained with less computation and measurement point. The validity and effectiveness of the algorithm was tested by numerical simulations. The results convinced us that the develop algorithm can be used for surface measurement and tool path planning for NC machining.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.380-385
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• 1990

This Paper presents a general algorithm for the parameter estimation of an antoregressive moving average process observed in additive white noise. The algorithm is based on the Gauss-Newton recursive prediction error method. For the parameter estimation, the output measurement is modelled as an innovation process using the spectral factorization, so that noise free RPE ARMA estimation can be used. Using apriori known properties leads to algorithm with smaller computation and better accuracy be the parsimony principle. Computer simulation examples show the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.25-32
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• 2017

Most of weapon systems use aided navigation system which integrates inertial navigation and aiding sensors to compensate the INS errors increasing with the passage of time. Various aid sensors can be applied such as Global Navigation Satellite System (GNSS), radar, barometer, etc., but there might exist time delay caused by signal processing or transferring aid information. This time delay leads out-of-sequence measurements (OOSM) systems. Previously, optimal and suboptimal measurment update method for OOSM systems, where the time delay length are known, are proposed. However, previous algorithm does not guarantee the positive definite property of covariance matrix. In order to improve numerical stability for aided navigation using delayed-measurement, this paper proposes a new measurement covariance update algorithm be similar to Joseph-form in Kalman filter. Futhermore, we propose how to implement it in indirect feedback Kalman filter structure, which is commonly used in aided navigation systems, for time-delayed measurement systems. Simulation and vehicle test results show effectiveness of a proposed algorithm.