• Structural Engineering and Mechanics
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• v.76 no.1
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• pp.101-114
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• 2020

In this paper, an improved experience-based learning algorithm (EBL), termed as IEBL, is proposed to solve the nonlinear hysteretic parameter identification problem with Bouc-Wen model. A quasi-opposition-based learning mechanism and new updating equations are introduced to improve both the exploration and exploitation abilities of the algorithm. Numerical studies on a single-degree-of-freedom system without/with viscous damping are conducted to investigate the efficiency and robustness of the proposed algorithm. A laboratory test of seven lead-filled steel tube dampers is presented and their hysteretic parameters are also successfully identified with normalized mean square error values less than 2.97%. Both numerical and laboratory results confirm that, in comparison with EBL, CMFOA, SSA, and Jaya, the IEBL is superior in nonlinear hysteretic parameter identification in terms of convergence and accuracy even under measurement noise.

• 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.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.469-474
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• 2000

A sliding mode control method using the parameterization of both the hyperplane and the compensator for output feedback and reduced observer is presented for rotational inverted pendulums. This control strategy overcomes the problem of unattainable velocity state which is resulted from severe noise of analogue sense and constructs numerical algorithms designs of dynamic output feedback sliding mode hyperplane and controller. The result of the experiment shows the superior performance compared with the LQ controller and the robustness with respect to both tapping disturbances and certain initial conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.6
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• pp.475-484
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• 1990

This paper proposes a method for the implementation of a power line communication equipment using power line synchronization in a direct-sequence spread spectrum communication system. In order to implement a network using a power line as a transmission channel we have investigated the utilization of direct-sequence speread spctrum which gives such advantages as robustness against narrow-band interference and noise, and realization of multiple access. In a power line, however, complexity of synchronization makes it difficult to realize a multiple access and cost down and system simplification. The proposed technique of power line synchronization makes it possible to get cost down and system size small, and the realization of multiple communication can be achieved by the addition of address setting circuit.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.274-274
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• 2000

In the future, the convenient speech command system will become an widely-using interface in automation systems. But the previous research in speech recognition didn't give satisfactory recognition results for the practical realization in the noise environment. The purpose of this research is the development of a practical system, which reliably recognizes the speech command of the registered users, by complementing an existing research which used the image information with the speech signal. For the lip-reading feature extraction from a image, we used the DWT(Discrete Wavelet Transform), which reduces the size and gives useful characteristics of the original image. And to enhance the robustness to the environmental changes of speakers, we acquired the speech signal by stereo method. We designed an economic stand-alone system, which adopted a Bt829 and an AD1819B with a TMS320C31 DSP based add-on board.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.2
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• pp.34-39
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• 2005

The precision stage is an essential device for optic fiber assembly systems, micro machines and semiconductor equipments. A new piezoelectric inchworm type actuator is proposed to implement an actuator-integrated long-stroke linear stage. An in-and-quadrature phase (I/Q) heterodyne interferometer is developed as a feedback sensor of a servo system, and a synchronized counting method is proposed. The proposed measurement system can measure the accurate position of fast moving object with robustness to external sensing noise from actuator vibration. The developed servo stage will be applied to optic fiber device assembly system.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.5
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• pp.127-134
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• 2007

Presented in the paper is an algorithm to generate a section curve by slicing a point cloud including tens of thousands of points. Although, there have been previous research results on the slicing problem, they are quite sensitive on the density variations of the point cloud, as well as on the local noise in the point cloud. To relive the difficulties, three technological requirements are identified; 1) dominant point sampling, 2) avoiding local vibration, and 3) robustness on the density changes. To satisfy these requirements, we propose a new slicing algorithm which is based on a node-sphere diagram. The algorithm has been implemented and tested with various examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3050-3065
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• 2016

Neural networks (NNs) are extensively used in applications requiring signal classification and regression analysis. In this paper, a NN based threshold selection algorithm for 60 GHz millimeter wave (MMW) time of arrival (TOA) estimation using an energy detector (ED) is proposed which is based on the skewness, kurtosis, and curl of the received energy block values. The best normalized threshold for a given signal-to-noise ratio (SNR) is determined, and the influence of the integration period and channel on the performance is investigated. Results are presented which show that the proposed NN based algorithm provides superior precision and better robustness than other ED based algorithms over a wide range of SNR values. Further, it is independent of the integration period and channel model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.558-561
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding Process in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noise such spatter and arc light. The adaptive Hough transformation was used to extract the laser stripe and to obtain specific weld points In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1711-1725
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• 2014

Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.