• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1377-1382
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• 2018

In the marine environment, many clutters have similar features with the marine targets due to the diverse changes of the air temperature, water temperature, various weather and seasons. Also, the clutters in the ground environment have similar features due to the same reason. In this paper, we proposed a robust Hybrid Machine Character (HMC) method to classify the targets from the clutters in the infrared images for the various environments. The proposed HMC method adopts human's multiple personality utilization and the CNN ensemble method to classify the targets in the ground and marine environments. This method uses an advantage of the each environmental training model. Experimental results demonstrate that the proposed method has better success rate to classify the targets and clutters than previously proposed CNN classification method.

• International journal of steel structures
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• v.18 no.4
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• pp.1410-1419
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• 2018

Recently, a repair method by bonding patch plates is being applied to corroded steel structures. However, one of the issues of patch plate bonding repair is the brittle debonding of the patch plates. Generally, when the delamination of the patch plates occurs, the composite effect acting between the steel members and patch plates abruptly decreases. Therefore, to prevent the brittle debonding of the patch plates, a repair method combining an adhesive and stud bolts is proposed. Till date, tensile and compressive tests have been performed for the proposed method. In this study, plate bending tests were conducted to verify the effectiveness of this method under bending conditions. Furthermore, two types of epoxy resin-based adhesives were prepared to evaluate the effectiveness of the proposed method with different adhesive properties. The test results show that the proposed method is able to prevent the brittle debonding of the patch plates in the case of both epoxy resins.

• Smart Structures and Systems
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• v.33 no.1
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• pp.1-16
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• 2024

The investigation on vehicle-bridge coupling system (VBCS) is crucial in bridge design, bridge condition evaluation, and vehicle overload control. A real-time hybrid testing (RTHT) method for VBCS (RTHT-VBCS) is proposed in this paper for accurately and economically disclosing the dynamic performance of VBCSs. In the proposed method, one of the carriages is chosen as the experimental substructure loaded by servo-hydraulic actuator loading system in the laboratory, and the remaining carriages as well as the bridge structure are chosen as the numerical substructure numerically simulated in one computer. The numerical substructure and the experimental substructure are synchronized at their coupling points in terms of force equilibrium and deformation compatibility. Compared to the traditional iteration experimental method and the numerical simulation method, the proposed RTHT-VBCS method could not only obtain the dynamic response of VBCS, but also economically analyze various working conditions. Firstly, the theory of RTHT-VBCS is proposed. Secondly, numerical models of VBCS for RTHT method are presented. Finally, the feasibility and accuracy of the RTHT-VBCS are preliminarily validated by real-time hybrid simulations (RTHSs). It is shown that, the proposed RTHT-VBCS is feasible and shows great advantages over the traditional methods, and the proposed models can effectively represent the VBCS for RTHT method in terms of the force equilibrium and deformation compatibility at the coupling point. It is shown that the results of the single-degree-of-freedom model and the train vehicle model are match well with the referenced results. The RTHS results preliminarily prove the effectiveness and accuracy of the proposed RTHT-VBCS.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2807-2810
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• 2003

In this paper, we propose a fuzzy control method for improving the control performance by automatically tuning the scaling factor. The proposed method is that automatically tune the input scaling factor and the output scaling factor of fuzzy logic system through neural network. Used neural network is ADALINE (ADAptive Linear NEron) neural network with delayed input. ADALINE neural network has simple construct, superior learning capacity and small computation time. In order to verify the effectiveness of the proposed control method, we performed simulation. The results showed that the proposed control method improves considerably on the environment of the disturbance.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.13-16
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• 2000

In this paper, we propose hybrid control method of neural network using the 3-point search algorithm. Proposed control method is searched the weight using the 3-point search algorithm for off-line then control the on-line. In order to verify the usefulness of the proposed method, we simulated the proposed control method with one link manipulator system and confirmed the excellency.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2262-2267
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• 2017

A new force expression on dielectrics subjected to electric field is proposed in this paper. It is the electric version of the equivalent magnetizing current method in magnetic field. From the idea of electromagnetic duality, virtual equivalent electrifying magnetic current method is conjectured in the field of dielectric force problem. Numerical results show that the proposed method has good agreements with the conventional methods. The merits and demerits of the proposed method are also discussed.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1671-1677
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• 2017

In this paper, we propose a machine learning method for random noise removal in image deblurring. The proposed method uses a logistic regression to select reliable data to use them, and, at the same time, to exclude data, which seem to be corrupted by random noise, in the deblurring process. The proposed method uses commonly available images as training data. Simulation results show an improved performance of the proposed method, as compared with the median filtering based reliable data selection method.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.12-17
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• 1991

In this paper, a variable structure system control method is proposed to the trajectory control of robot arm. A proposed method uses nonlinear switching function and saturation function. Furthermore, learning control method uses to decrease of the following error. The computer simulation results show that the chattering and the following error decrease and is improved the control the performance by a proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1175-1180
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• 1991

The purpose of this paper is to improve the matching accuracy in identifying corresponding points in the area-based matching for the processing of stereo vision. For the selection of window size, a new method is proposed based on frequency domain analysis. The effectiveness of the proposed method is confirmed through a series of experiments. To overcome disproportionate distortion in stereo image pair, a new matching method using the warped window is also proposed. In the algorithm, the window is warped according to imaging geometry. Experiments on a synthetic image show that the matching accuracy is improved by 14.1% and 4.2% over the rectangular window method and image warping method each.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.937-940
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• 1992

A cost-saving feeding rate contro method for a batch reaction process is proposed by reconfigurating the flow rate control loop where the feeding rate is estimated by differentiating weight measurement. While the existing control methods require either a flow rate measurement device or a flow rate estimator, the proposed method is devised not to require neither of these facilities by directly controlling the tank weight with a time-varying set point. Experimental evaluation in a pilot-scale unit shows that the proposed method can significantly reduce the actuator hunting of the existing method where the flow rate is estimated by differentiating the weight measurement.