• Nuclear Engineering and Technology
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• v.20 no.1
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• pp.47-53
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• 1988

The objective of this study is to evaluate the reliability of the High Head Safety Injection System (HHIS) of KNU 5, 6, 7 and 8 following the removal of safety injection signal (s-signal) from the mini-flow bypass line valves of charging/safety injection pumps. The unavailability of HHSIS and the rupture probability of a charging/safety injection pump have been computed for two different cases; with s-signal on and removed. The results show that when the s-signal is removed from the mini-flow bypass line valves, the unavailability of HHSIS slightly increases while the rupture probability of a charging/safety injection pump is significantly reduced. Hence, based upon the results of this study we conclude that it is more reasonable to remove the s-signal from the mini-flow bypass line valves of KNU 5, 6, 7 and 8 in the normal plant operation. And to improve the availability of HHSIS, the modification of operational procedures and the emphasis on operator training are recommended.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1796_1797
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• 2009

원자력발전소의 금속파편감시설비는 원자로냉각 재계통에서 발생되는 충격신호에 대한 정보를 운영자에게 제공하여, 금속이물질로 인한 관련 구조물 파손을 미연에 방지하기 위한 설비이다. 운전 중에 발생되는 충격신호 중 대부분을 차지하는 거짓경보는 열팽창이나 구조물마찰에 의한 신호이나, 국내외에 설치되어 운전 중인 금속파편감시설비에는 열팽창과 구조물마찰에 의한 충격신호를 판단할 수 있는 알고리즘이 탑재되어 있지 않다. 따라서 본 연구에서는 대부분의 거짓 경보를 발생시키는 열팽창 및 구조물마찰에 의한 충격신호를 신호 검출단계에서 배제할 수 있는 알고리즘을 제시하고자 한다.

• Composites Research
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• v.15 no.5
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• pp.1-6
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• 2002

When compared to other composite materials such as FRP and MMC, hybrid composite material is more attractive one due to the high specific strength and the resistance to fatigue. However, the fracture mechanism of hybrid composite material is extremely complicated because of the bonding structure of metals and FRP. Recently, nondestructive technique has been used to evaluate the fracture mechanism of these composite materials. In this study. AE technique has been used to clarify the fracture mechanism and the degree of damage for Al 7075/CFRP hybrid composite material. It was found that AE event, energy and amplitude among AE parameters were effective to evaluate fracture process of Al 7075/CFRP composite material. In addition, the relationship between the AE signal and the characteristics of failure surface using optical microscope was discussed.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.191-191
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• 2004

베어링은 회전기계에서 가장 일반적인 구성요소로 베어링의 초기 결함 또는 퇴화현상이 사전에 발견되지 않으면 회전기계의 고장 또는 파손으로 엄청난 손실이 초래될 수 있다. 베어링의 초기 결함을 검출하기 위한 가장 보편적인 방법으로 베어링 진동신호의 특징적인 패턴을 검출하는 것이다.(중략)

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.04a
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• pp.328-333
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• 1991

가공 프로세스의 감시에 대한 많은 연구는 주로 과부하, 공구파손, 공구마멸, 채터링, 충돌 승을 대상으로 한 것으로, AE(Acoustic Emission), 모터전류, 절삭력, 진동, 절삭온 도 등의 신호를 감지한 뒤 이들 신호에 각종 신호 처리를 행하여 가공 상태에 대한 정보를 추출하고, 그것에 근거한 감시를 하고 있다. 작업중 감시연구에서 주로 제기 되는 문제는 공구교환이나 공작물 교환에 무관하게 또 작업에 지장을 주지 않으면서 이들 신호를 감지해야 하는 점과 감시처리의 신뢰성을 높여야 하는 점이다. 본 연구에서는 NC프로그램으로 부터 얻은 예측정보를 이용해서 선삭가공에서 감시 시스템의 성능향상을 시도 하였다. 예측정보는 감시코드의 형태로 각 NC블럭에 추가하여 실시간 감시에서 작업의 상태를 인식할 때 참고 정보로 활용하기 때문에 감시에 대한 신뢰성을 높일 수 있었다. 감시신호로는 이송축 직류 서보 모터의 전류를 사용하였다. 전체적인 감시 시스템의 프로그래밍 언어로는 C 를 사용하여, 실시간 감시처리를 가능하게 하였다.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.104.2-104.2
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• 2005

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.34-41
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• 1998

An integrated circuit for magnetic stripe storage system is implemented. All the analog and digital circuits are integrated in one chip. The analog block contains preamplifier, peak detecter, comparator and reference generater. And digital block includes reference window signal generater, up/down counter for F/2F signal measurement, bit-error detection logic, and control logic. Both the encoding and decoding functions for F/2F signal processing are provided. An AGC(automatic gain control) circuit which was included in conventional circuits is eliminated due to optimized circuit design. Misreading prevention circuits are also proposed by fixing up new reference bit when broken bits are detected. The prototype chip is implemented using $0.8{\mu}m$ N-well CMOS technology and operates from 3.3 V to 7.5 V of supply voltage. It occupies a die area of $3.04mm^2(1.6mm{\times}1.9mm)$ and dissipates 8 mW with a 5 V supply voltage.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.445-454
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• 2003

Health monitoring is a major concern not only in the design and manufacturing but also in service stages for composite laminated structures. Excessive loads or low velocity impact can cause matrix cracks and delaminations that may severely degrade the load carrying capability of the composite laminated structures. To develop the health monitoring techniques providing on-line diagnostics of smart composite structures can be helpful in keeping the composite structures sound during their service. In this study, we discuss the signal processing techniques and some applications for health monitoring of composite structures using piezoceramic sensors and fiber optic sensors.