• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2007년도 추계종합학술대회
• /
• pp.231-234
• /
• 2007

자기적 원리를 이용한 Magnetic Sensor는 자기를 전기로 변환하는 Element로서 산업분야, 대학 및 연구소 등에서 대단히 폭 넓게 사용되고 있으나 아직 국내에서 체계적으로 양산 되고 있지 않은 상태이고 제작기술 수준 역시 선진국에 비해 저조하며 Excitation Current, Excitation Frequency, 코어의 투자율 등의 변화에 의해 센서 출력에 왜곡현상이 나타나거나 부하현상이 발생하여 이 때문에 최소 측정 범위가 제한된다. 따라서 양호한 출력신호를 감지하기 위해서는 신호변환장치 의 성능이 뒷받침되어야 한다. 본 논문 에서는 유도성 근접 센서를 이용 하여 신호변환장치 회로를 설계하여 금속표면에 페인트 두께를 마이크로 단위로 검출, 측정 하는 제어 시스템을 연구하는데 그 목적을 둔다.

• 대한의용생체공학회:의공학회지
• /
• 제36권1호
• /
• pp.31-36
• /
• 2015

In this study, we evaluated the effects of static magnetic fields of earphones and headphones on pacemakers and implantable cardioverter defibrillators(ICDs). Five pacemakers and three ICDs were subjected to in-vitro test with three headphones which were an in-ear earphone, clip-on headphone, and closed-back headphone. Each implantable device was placed in close proximity(within 3 mm) to the ear-pad of each of the earphone and headphones for 3 min. As a result, no effects were observed on the pacemakers for the earphone and headphones during the test, but an effect was observed on one ICD for the clip-on and closed-back headphone during the test. When the ICD was placed in close proximity to the headphones, the ICD temporarily suspended functions of tachyarrhythmia detection and therapy. The effect was not observed in this study when the headphones were at least 2 cm from the ICD. Based on these findings, patients with ICDs should be advised to keep earphones and headphones at least 2 cm apart from their ICDs.

• 한국융합학회논문지
• /
• 제11권10호
• /
• pp.63-69
• /
• 2020

본 논문에서는 저속으로 불규칙하게 움직이는 인체의 심박신호를 감지하기 할 수 있어 웨어러블 디바이스에 적용 가능한 소형 마이크로파 센서를 제안하였다. 이를 위해 2.4 GHz ISM 대역에서 평형 구조를 갖는 마이크로스트립 방사 패치들과 자체발진 검출회로 및 귀환회로가 구성되었다. 이론 전개와 시뮬레이션을 통해 제안된 구조의 타당성을 확인하였고 제작된 시제품을 측정하였다. 회로의 보드는 65mm × 85㎟의 작은 크기이며, 간단한 고주파 회로구조로 60mW 수준의 작은 전력을 소모한다. 센서와 직선거리 2~30mm, 측면 좌우 거리 ±20mm 범위 내에서 저속(0.5Hz)으로 움직이는 인체로부터 심박신호를 얻을 수 있었다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.121.4-121
• /
• 2001

We propose an off-line methodology for detecting a faulty backup roll that generates eccentricity components, under the condition that the feeding velocity, equivalently the angular velocity of roll, is not constant. From a newly devised speed angle conversion algorithm, we transform all process data into those of a virtual process under a constant feeding speed. This indirectly way, we can apply a spectral analysis to the original process. In addition, we develop an online detection method of roll eccentricity based on newly designed PLG sensor. This PLG sensor is robust because of applying magnetic proximity sensnors and non-contact measurement method.

• 한국전기전자재료학회논문지
• /
• 제30권4호
• /
• pp.253-257
• /
• 2017

Nowadays, it is increasingly important to detect whether cables are live for the operator's safety if there is a sudden power failure. It is especially hard to detect the electrical field of an underground line because of shielding. This paper on detection of live-line states in cables studied the detection characteristics of the change in the magnetic field and axis as the frequency, voltage, and distance at the same load are changed using 3 axes. A search coil type was used as a magnetic field sensor with non-contact. We found that magnetic fields decrease proportionally to the square of the distance and the decrease of rated voltage with load effected to magnetic field. The magnetic field was detected by 3-axis sensors given correct proximity, but appeared as noise components beyond a distance of 2 cm.

• 대한화학회지
• /
• 제5권1호
• /
• pp.26-28
• /
• 1961

Microgram quantities of thallirum in meteorites, rocks, minerals, alloys and biological samples have been analyzed by rapid neutron activation analysis. A l0-minute radiochemical separation procedure coupled with a gas-flow proportional detector for 4.2-minute half life measurement and a gamma or beta scintillation detector placed in close proximity to the sample permitted detection of the 4.2-min Tl206. Samples were irradiated for 10-minutes at a thermal neutron flux of approximately $0.95{\times}10^{11}$ neutron-$cm^{-2}-sec^{-1}.$ The low limits of detection was about $10^{-7}$ gm of thallium.

• Journal of Positioning, Navigation, and Timing
• /
• 제10권3호
• /
• pp.169-177
• /
• 2021

In this paper, we propose a novel global navigation satellite system (GNSS) spoofing detection technique through an array antenna-based direction of arrival (DoA) estimation of satellite and spoofer. Specifically, we consider a sophisticated GNSS spoofing attack scenario where the spoofer can accurately mimic the multiple pseudo-random number (PRN) signals since the spoofer has its own GNSS receiver and knows the location of the target receiver in advance. The target GNSS receiver precisely estimates the DoA of all PRN signals using compressed sensing-based orthogonal matching pursuit (OMP) even with a small number of samples, and it performs spoofing detection from the DoA estimation results of all PRN signals. In addition, considering the initial situation of a sophisticated spoofing attack scenario, we designed the algorithm to have high spoofing detection performance regardless of the relative spoofing signal power. Therefore, we do not consider the assumption in which the power of the spoofing signal is about 3 dB greater than that of the authentic signal. Then, we introduce design parameters to get high true detection probability and low false alarm probability in tandem by considering the condition for the presence of signal sources and the proximity of the DoA between authentic signals. Through computer simulations, we compare the DoA estimation performance between the conventional signal direction estimation method and the OMP algorithm in few samples. Finally, we show in the sophisticated spoofing attack scenario that the proposed spoofing detection technique using OMP-based estimated DoA of all PRN signals outperforms the conventional spoofing detection scheme in terms of true detection and false alarm probability.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권3호
• /
• pp.1264-1286
• /
• 2018

In this paper, a novel background prior-based salient object detection framework is proposed to deal with images those are more complicated. We take the superpixels located in four borders into consideration and exploit a mechanism based on image boundary information to remove the foreground noises, which are used to form the background prior. Afterward, an initial foreground prior is obtained by selecting superpixels that are the most dissimilar to the background prior. To determine the regions of foreground and background based on the prior of them, a threshold is needed in this process. According to a fixed threshold, the remaining superpixels are iteratively assigned based on their proximity to the foreground or background prior. As the threshold changes, different foreground priors generate multiple different partitions that are assigned a likelihood of being foreground. Last, all segments are combined into a saliency map based on the idea of similarity voting. Experiments on five benchmark databases demonstrate the proposed method performs well when it compares with the state-of-the-art methods in terms of accuracy and robustness.

• 센서학회지
• /
• 제21권3호
• /
• pp.211-216
• /
• 2012

Fires are the most common disaster and early fire detection is of great importance to minimize the consequent damage. Simple sensors including smoke detectors are widely used for the purpose but they are able to sense fires only at close proximity. Recently, due to the rapid advances of relevant technologies, vision-based fire sensing has attracted growing attention. In this paper, a novel visual sensing technique to automatically detect fire is presented. The proposed technique consists of multiple steps of image processing: pixel-level, block-level, and frame level. At the first step, fire flame pixel candidates are selected based on their color values in YIQ space from the image of a camera which is installed as a vision sensor at a fire scene. At the second step, the dynamic parts of flames are extracted by comparing two consecutive images. These parts are then represented in regularly divided image blocks to reduce pixel-level detection error and simplify following processing. Finally, the temporal change of the detected blocks is analyzed to confirm the spread of fire. The proposed technique was tested using real fire images and it worked quite reliably.

• 한국기계가공학회지
• /
• 제20권12호
• /
• pp.1-7
• /
• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.