• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.31-37
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• 2007

This paper presents a ballistic lead-computation method which utilizes automatic video tracking, tracking assistance and roll uncoupling. The method is able to improve the firing accuracy of army fighting vehicles such as main battle tanks. In the experiment, the efficiency of the proposed method is evaluated by an error analysis in real operating environment. The proposed method has been applied to the fire control system of a military vehicle and proved through the development test of the vehicle.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1030-1032
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• 1998

In this paper, an efficient feature vector extraction method and MLP neural network are utilized to automatically detect and classify power quality disturbances, where the proposed classification procedure consists of the following three parts: i.e., (i) PQ disturbance detection using discrete wavelet transform. (ii) feature vector extraction from the detected disturbance. using several methods, such as FFT, DWT, Fisher's criterion. etc.. and (iii) classification of the corresponding type of each PQ disturbance by recognizing the pattern of the extracted feature vector. To demonstrate the performance and, applicability of the proposed classification algorithm. some test results obtained by analyzing 10-class PQ disturbances are also provided.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.157-158
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• 2019

Reinforcing bars are an important material for tensile strength of structures. For this reason, the inspection of the reinforcing bars confirming the layout and omission is very important for the safety of the structures. However, the current method of inspecting of the reinforcing bars through photographs of specific areas is difficult to identify condition all reinforcing bars. And It is also difficult to confirm after completion of a building. Therefore, reinforcing bar inspection using 3D scanner is required for automation of rebar inspection and database construction. For this purpose, this study test application of automated inspection method for rebar inspection using 3D scanner and discuss the effect of this method.

• Computers and Concrete
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• v.9 no.4
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• pp.293-310
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• 2012

This paper discusses a new constitutive model called the high-rate brittle microplane (HRBM) model and also presents the details of a new software package called the Virtual Materials Laboratory (VML). The VML software package was developed to address the challenges of fitting complex material models such as the HRBM model to material property test data and to study the behavior of those models under a wide variety of stress- and strain-paths. VML employs Continuous Evolutionary Algorithms (CEA) in conjunction with gradient search methods to create automatic fitting algorithms to determine constitutive model parameters. The VML code is used to fit the new HRBM model to a well-characterized conventional strength concrete called WES5000. Finally, the ability of the new HRBM model to provide high-fidelity simulations of material property experiments is demonstrated by comparing HRBM simulations to laboratory material property data.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.730-734
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• 2001

In this study in order to confirm the algorithms that are suggested from paper (I) as the experimental result, as the applied results of the hydraulic servo system are very strong a non-linearity of the fluid in the computer simulation, the real-time adaptive learning control algorithms is validated. The evolutionary strategy has characteristics that are automatically. adjusted in search regions with natural competition among many individuals. The error that is generated from the dynamic system is applied to the mutation equation. Competitive individuals are reduced with automatic adjustments of the search region in accord with the error. In this paper, the individual parents and offspring can be reduced in order to apply evolutionary algorithms in real-time as the description of the paper (I). The possibility of a new approaching algorithm that is suggested from the computer simulation of the paper (I) would be proved as the verification of a real-time test and the consideration its influence from the actual experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.119-123
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• 1996

The demands for robotic and automatic system are continually increasing in manufacturing fields. There were so many studies to monitor and predict system, but it were mainly relied upon measuring of cutting force, current of motor spindle and using acoustic sensor, etc. In this study digital image of time series sequence was acquired taking advantage of optical technique. Then, mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR model was selected for system model, fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, we found there was a system stability.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.150-155
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• 2005

In recent years, as the demands of VBNS(Very high speed Backbone Network Service) and VDSL(Very high-data rate Digital Subscriber Line) increase, the development of kernel parts of optical communication such as PLC(Planar Light Circuit), Coupler, WDM elements increase. The alignment and the attachment technology are very important to fabricate the optical elements for communication. In this paper, the mechanism of rotational stage are studied. with the three different method and the results of them are applied to the design of the system. The performance test of resolution and travel is performed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.387-392
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• 2002

It is very important to measure linear cycle plane positioning accuracy of NC lathes as they affect those of all other machines machined by them in industries. For example, if the linear cycle plane positioning accuracy of each axes directions is bad, the accuracy of works will be wrong and the change-ability will be bad in the assembly of machine parts. In this paper, computer software systems are organized to measure linear displacements of ATC(Automatic tool changer) of NC lathes using linear scale and time pulses comming out from computer in order to get data at constant time intervals from the sensors. And each sets of error data gotten from the test is expressed to plots by computer treatment and the results of linear cycle plane positioning error motion estimated to numerics by statistical treatments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.6 s.261
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• pp.651-658
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• 2007

A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.652-658
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• 1997

Coagulant feeding control is very important in the water treatment process. Coagulant feeding is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and so on. However, since the process of chemical reaction has not been clarified so far, coagulant dosing rate has been decided by jar-test. In order to overcome the difficulty mentioned above, Fuzzy Neural Network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to the automatic determination of coagulant dosing rate. This algorithm can automatically identify the if-then rules, tune the membership functions by utilizing expert's experimental data. The proposed scheme is evaluated by computer simulation and interfaced with coagulant feeder operated by magnetic flowmeter, control valve and PLC. It is shown that coagulant feeding according to real time sensing of water quality is very effective.