• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.5
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• pp.401-406
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• 2008

Recently, portable magnetic sensors with high sensitivity are strongly required for various applications such as biosensor, nondestructive testing and directional sensor. A novel magnetic sensor system was developed by utilizing giant magnetoimpedance(MI) effect of soft magnetic ribbons. The sensor system consists of sensing head of $Co_{66}Fe_{4}Si_{15}B_{15}$ ribbon having asymmetric MI characteristics through exchange coupling produced by field-annealing in open air and circuit for signal processing. The sensor system showed almost linear characteristics in dynamic range of $-1\;Oe\;{\sim}\;1\;Oe$ and sensitivity of 10.5 V/Oe. The sensor was applicable to nondestructive testing system to detect defects in wire ropes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1547-1548
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• 2015

본 연구에서는 홀센서를 이용하여 크레인 와이어로프의 결함 탐지를 위하여 제작된 결함탐지 시스템의 성능 개선을 위한 방안에 대하여 연구하였다. 기존의 센서 보드 대신 플렉시블 보드를 제작하고 홀센서를 6개에서 10개로 늘려 장착하여 센서헤더부를 보완 제작하였다. 또한, 검사자가 한 눈에 알아보기 쉽도록 하기 위하여 결함 신호 측정 구간을 6개 구간에서 2개 구간으로 바꾸었으며, 정밀한 실험과 정확한 검증을 위하여 테스트베드를 제작하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.149-151
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• 2009

본 논문에서는 이동이 힘들거나 자주 건강관리가 필요한 노약자나 임산부들에게 좀 더 신속하고 빠른 진단 서비스를 제공하기 위해 단말기에서 맥박을 측정하여 Bluetooth를 통하여 모바일 폰에 전송하고 원격에서 모바일 폰을 통해 전송된 맥박파형 데이터를 분석하고자 한다. 팔목에 착용하는 형태의 단말기에는 체온측정을 위한 온도센서, 맥박측정을 위한 Piezo Vibration Sensor, 움직임 체크를 위한 가속도센서와 자이로센서가 장착되어있다. 이 센서들을 이용하여 측정된 데이터들을 모바일 폰의 Wi-Fi를 통해 서버로 전송하여 원격에서 의사가 담당환자를 체크할 수 있도록 하고자 한다.

• Journal of the Korean Magnetics Society
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• v.20 no.4
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• pp.167-172
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• 2010

To meet on going challenges in nano-biomedical technology, the convergence of "spintronics", "biomedical" technology is a major break through in imaging, diagnosis and therapy, high-throughput genomic analysis. Especially magnetic bioassay is one of crucial devices for early diagnosis of specific analytes, point-of-care and U-health care application. In this paper, current status on high resolution magnetic sensors for bioassay and on-chip magnets for biomolecule transportation will be reviewed.

• Journal of the Korean Vacuum Society
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• v.14 no.3
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• pp.110-114
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• 2005

This study proposes an accurate method of monitoring precursor consumption in chemical vapor deposition (CVD) systems. Since precursor costs are significant, finding an efficient method to monitor precursor consumption is necessary One example is the use of non-contact and inexpensive ultrasonic sensors for determining the liquid level in a container. In this study, sensors based on ultrasonic techniques have been developed for monitoring the precursor consumption in a CVD system. Moreover, the prototype sensors developed in this study can be useful in the field of semiconductors.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.6
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• pp.179-187
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• 2010

Corrosion of rebar embedded reinforced concrete is the main cause of collapse and degradation of reinforced concrete structure. Degradation occurs in reinforced concrete structures from corrosion caused by the Chloride that the damage other than the severe degradation of the structure in terms of maintenance and construction when the huge expense required and deciding terms is hard. Therefore, early detection of rebar corrosion is important for efficient maintenance and repairing and planning. Meanwhile, how to evaluate the corrosion of the non-destructive measurements have been used a lot. In particular CM-II (corrosion meter) is used to measurement the natural potential, polarization resistance and the resistivity of the concrete, but has some disadvantages. Embedded mini-sensor has been developed in order to overcome these disadvantages. So Measurement corrosion for using the mini-sensor compares with the measured results CM-II (corrosion meter), the developed mini-sensor verify the validity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.129-136
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• 2019

In this study, the magnetic flux leakage technique was applied to diagnose steel plate damage, imaging technique was applied through those signals. Steel plate specimens with different thicknesses were prepared for the imaging the magnetic flux leakage signal, and 6 different depths of damage were artificially processed at the same locations on each specimen. The sensor head consist hall sensor and magnetization yoke was fabricated to magnetize the steel plate specimen and measure the magnetic flux leakage signal. In order to remove the noise and increase the resolution of the image in the signal collected from the hall sensor, various of signal processing was performed. P-P value was analyzed for each channel to analyze the magnetic flux leakage signals measured from each damaged part. Based on the above processed signals and analysis, it was converted into heatmap image. Through this, it was possible to identify the damage on the steel plate at glance by imaging magnetic flux leakage signal.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.41-42
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• 2014

최근 우리나라에서는 새로운 항만설계 혹은 변경 등을 함에 있어 해상교통안전진단을 우선적으로 실시하여 해상교통의 안전을 도모하고 있다. 이 해상교통안전진단은 자연환경 및 해상교통조사, 선박조종시뮬레이션, 해상교통류 시뮬레이션, 계류안전성, 그리고 안전대책 등으로 구성되어 있다. 그 중 선박조종과 관련된 선박조종시뮬레이션이 아주 중요하다. 이것은 해당 항만에서 선박 조종을 담당하는 도선사 혹은 선장들에게 직접적인 관련이 있기 때문이다. 선박조종시뮬레이션에서 근접도 평가는 항로 혹은 접이안 조선의 안전도를 평가하는 중요한 요소이다. 그러나 근접도 평가는 시뮬레이션의 횟수를 얼마 이상으로 할 때 제대로 된 평가를 할 수 있는가 하는 점은 밝혀져 있지 않다. 중심극한정리에 따르면 30회 이상이면 표본 집단은 정규분포를

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.809-816
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• 2008

With increasing demands for reducing cost of maintenance which can detect machine fault automatically; low cost and intelligent functionality sensors are required. Rapid developments, in semiconductor, computing, and communication have led to a new generation of sensor called "smart" sensors with functionality and intelligence. The purpose of this research is comparison of machine fault classification between general analyzer signals and smart sensor signals. Three types of sensors are used in induction motors faults diagnosis, which are vibration, current and flux. Classification results are satisfied.