• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.235-241
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• 1993

생산시스템의 요소기술은 단계별로 설계, 가공, 검사에 관한것이 있으며 FMS, CIM과같은 생산시스템에서는 통가공 Cell의 효율을 극대화시키기 위한 기술로 지능화한 지능화기술은 전문가시스템(Expert System), 퍼지 이론 (Fuzzy logic)및 신경회로망(Neural Network)의 도입에 의해 활발히 이루어지고있다. 시스템의 지능화 를 위해서 가장 근간이 되는 기술은 그림 1.에 나타낸 바와 같이 지식(Knowledge) 기술과 센서(Sensor) 응용 기술이 며, 현재의 가공상태에 대한 정보는 전적으로 센서를 통해 얻어지며 상태판단은 축적된 지식을 바탕으 로 행해진다. 센서를 통해 얻어진 외부정보를 외부정보를 처리하는 인식(Recognition)이란 대상물의 존재를 아는 인지(Cognition)의 과정에서 한걸음 더 나아가 구체적인의미나 정보내용을 판정하는 것을 의미한다. 당 연구실에서는 이러한 기법들을 이용한 지능화된 공구마모/파손 감지에대한 연구를 수행중이다. 1차적으로 머시님센타의 엔드밀공정을 중심으로한 연구가 진행중이며 본 논문에서는 현재 연구실 차원에서 사용되고 있는 고가의 센서를 대체 할 수 있는 저가의 신뢰성 있는 센서의 이용에 촛점을 맞추어 패턴인식을 위한 절삭신호특성 분석 및 패턴 특성에대한 연구 결과를 소개하고자 한다.

• Journal of Korean Ophthalmic Optics Society
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• v.5 no.1
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• pp.199-203
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• 2000

Magnification shall large to test a surface of a contact lens also chromatic aberration and distortion to be removed. Be used of this study a contact lens analyzer is "CONTACT LENS ANALYZER CA-20", it is a good analyzer to suitable with surface test 16 times of big magnification and distortion.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.162-167
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• 2004

The low velocity impact characteristics of composite laminate curved beams are investigated to increase damage tolerance and reduce the deflection. Drop weight impact tests of the composite curved beam were performed with respect to pre-load, then the damage after impact was measured by macrography. Also, finite element analyses were performed using ABAQUS to investigate the stress state of composite curved beam with respect to pre-load and impact. From the investigation, it was found that pre-load of the composite curved beams had much influence on impact damage of the curved beam, which showed good agreement with the experiment results.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.197-201
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• 2011

검찰과 경찰에서는 압수수색을 통해 조사를 수행하는데, 기업들은 압수수색 수사를 받기 전에 회계 DB 및 회계 관련 파일 삭제, 파손 및 은닉하는 등의 문제점을 발생시키고 있다. 2008년 삼성화재 비자금 조성 사건과, 2009년 교하 복합커뮤니티 센터의 입찰비리 사건 등 기업회계장부의 포렌식 기술적용방법 문제 등이 발생하고 있다. 본 논문에서는 포렌식 수사 도구인 EnCase, FinalData 등을 연구하고, 기업의 회계 서버에 대해 압수수색 준비와 압수 수색, 획득 증거 분석 등의 절차를 연구한다. 기업의 회계 서버 압수수색 후에 디스크에서 포렌식 증거분석에서 실시되는 증거물 원본 파일보관, 원본성이 입증된 사본생성, 삭제 파일 검사 및 복원, 삭제 내용 확인, 원본 파일과의 대조를 실험을 한다. 본 연구 결과는 포렌식 기술발전에 기여하게 될 것이다.

• Journal of Korea Foundry Society
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• v.43 no.1
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• pp.3-10
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• 2023

This study was conducted to develop technology that can detect stomatal defects inside nonferrous metal products that may occur during die casting processes. Through this research, we intend to detect possible pores in the products in advance, block the distribution of defective products, and contribute to reducing possible losses due to damage to distributed products.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.30-36
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• 2004

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on the non-destructive testing methods of the composite materials has become an important research area for improving their reliability and safety. In this paper, the AE signal analyzer with the resonance circuit to extract the specified frequency of the acoustic emission signal were designed and fabricated. The noise levels of the fabricated AE signal analyzer by the disturbance such as impact or mechanical vibration had a very small value comparable to those of the conventional AE signal analyzer. Also, the fabricated AE signal analyzer was proved to have about the same crack detection capabilities with the conventional AE signal analyzer under the static and dynamic tensile tests of the composite materials.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.45-52
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• 2003

A number of stress corrosion cracks in turbine rotor disk keyway in power plants have been found and the necessity has been raised to detect and evaluate the cracks prior to the catastrophic failure of turbine disk. By ultrasonic RF signal analysis and using a neural network based on bark-propagation algorithm, we tried to evaluate the location, size and orientation of cracks around keyway. Because RF signals received from each reflector have a number of peaks, they were processed to have a single peak for each reflector. Using the processed RF signals, scan data that contain the information on the position of transducer and the arrival time of reflected waves from each reflector were obtained. The time difference between each reflector and the position of transducer extracted from the scan data were then applied to the back-propagation neural network. As a result, the neural network was found useful to evaluate the location, size and orientation of cracks initiated from keyway.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.737-745
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• 2008

Recent developments of process and measurement technology bring much interest to the online monitoring of process operations such as milling, grinding, broaching, etc. The objective of online monitoring systems is to detect process changes as early as possible. This is helpful in protecting facilities against unexpected failures and then preventing unnecessary loss. This paper investigates, when the process monitoring data are obtained as a profile, the monitoring performances of a statistical $T^2$-statistic and a feedforward neural network by using a wavelet transform. Numerical experiments using cutting force data presented by Axinte show that the proposed wavelet based $T^2$-test has an acceptable power in detecting profile changes. However, its operating characteristic is very sensitive to autocorrelation. On the contrary, compared with $T^2$-test, the neural network has more stable performance in the presence of autocorrelation. This indicates that an adaptive feature to analyze noises should be incorporated into the wavelet based $T^2$-test.

• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.2
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• pp.122-131
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• 1994

Journal bearings in the rotating machineries are vulnerable to the contamination or the insufficient supply of lubricating oil, which is likely to be the cause of unexpected shutdown or malfunction of these systems. Various destructive and nondestructive testing methods had been used for the reduction of maintenance cost and the operational safety problems due to the accidents related to bearing damages. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. Experimental schedules for the intervention of foreign particles was composed to be more quantitative and systematic than last study in consideration of minimum oil film thickness and particle size. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. Several parameters such as AE rms level, waveform, AE energy distribution and other AE event parameters are used for analysis and characterization of damage source. The results showed that the history of damage was well correlated with the changes of AE rms level and the type of damage source signal can be verified using other informations such as waveform, distributions of AE parameters etc.

• Composites Research
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• v.24 no.1
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• pp.24-30
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• 2011

Low-velocity impact can cause various damages which are mostly hidden inside the laminates or occur in the opposite side. Thus, these damages cannot be easily detected by visual inspection or conventional NDT systems. And if they occurred between the scheduled NDT periods, the possibilities of extensive damages or structural failure can be higher. Due to these reasons, the built-in NDT systems such as real-time impact monitoring system are required in the near future. In this paper, we studied the impact monitoring system consist of impact location detection and damage assessment techniques for composite flat and stiffened panel. In order to acquire the impact-induced acoustic signals, four multiplexed FBG sensors and high-speed FBG interrogator were used. And for development of the impact and damage occurrence detections, the neural networks and wavelet transforms were adopted. Finally, these algorithms were embodied using MATLAB and LabVIEW software for the user-friendly interface.