• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.97-104
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• 2008

Most of engine control systems for helicopter turboshaft engines are equipped with dual sensors. For the system with dual redundancy, analytic methods are used to detect faults based on the system dynamical model. Helicopter engine dynamics are affected by aerodynamic torque induced from the dynamics of the main rotor. In this paper an engine model including the rotor dynamics is constructed for the T700-GE-700 turboshaft engine powering UH-60 helicopter. The singular value decomposition(SVD) method is applied to the developed model in order to detect sensor faults. The SVD method which do not need an additional computation to generate residual uses the characteristics that the system outputs in direction of the left singular vector if an input is applied in direction of the right singular vector. Simulations show that the SVD method works well in detecting and isolating the sensor faults.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1677-1686
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• 2023

As the demand for the detection of special nuclear materials (SNMs) increases, the use of imaging instruments that can sensitively image both gamma-ray and neutron signatures has become necessary. This study compared the pulse shape discrimination (PSD) performance of gamma/neutron events when employing either a pixelated stilbene or a plastic (EJ-276) scintillator array coupled to a silicon photomultiplier (SiPM) array in a dual-particle imager. The stilbene array allowed a lower energy threshold above which neutron and gamma-ray events can be clearly distinguished. A greater number of events can, therefore, be used when forming both gamma-ray and neutron images, which shortens the time required to acquire the images by nearly seven times.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.79.2-79.2
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• 2019

We introduce Maemi Dual Field Telescope System (MDFTS) which is newly installed at Kyung Hee Astronomical Observatory (KHAO). MDFTS consists of two telescope tubes (40cm and 10cm), whose observing fields are aligned with different field of view, 15' x 11' and 83' x 63' respectively. We present the specification of instruments (telescope, mount, camera, and filter system) and the observation environment of KHAO. We expect that MDFTS can be used for transient survey e.g. Intensive Monitoring Survey of Nearby Galaxies (IMSNG). Based on observations conducted so far, the limiting magnitude of 40cm telescope in B-band is B_lim ~ 16 mag at 5-σ detection with 150 seconds total integration time under dark and clear observing condition. Also the integrated observing software for MDFTS, KAOS40 is now under developing.

• Current Optics and Photonics
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• v.8 no.2
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• pp.170-182
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• 2024

The dimensional accuracy and consistency of a dual oil circuit centrifugal fuel nozzle are important for fuel distribution and combustion efficiency in an engine combustion chamber. A point cloud measurement method was proposed to solve the geometric accuracy detection problem for the fuel nozzle. An improved variance focus measure operator was used to extract the depth point cloud. Compared with other traditional sharpness evaluation functions, the improved operator can generate the best evaluation curve, and has the least noise and the shortest calculation time. The experimental results of point cloud slicing measurement show that the best window size is 24 × 24 pixels. In the height measurement experiment of the standard sample block, the relative error is 2.32%, and in the fuel nozzle cone angle measurement experiment, the relative error is 2.46%, which can meet the high precision requirements of a dual oil circuit centrifugal fuel nozzle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.490-498
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• 2018

Panicle blight and seed rot disease caused mainly by Burkholderia glumae and Burkholderia gladioli is threatening rice cultivation worldwide. The bacteria have been reported as seed-borne pathogens from rice. Accurate detection of both pathogens on the seeds is very important for limiting the disease dissemination. Novel primer pairs targeting specific molecular markers were developed for the robust detection of B. glumae and B. gladioli. The designed primers were specific in detecting the target species with no apparent cross-reactions with other related Burkholderia species at the expected product size. Both primer pairs displayed a high degree of sensitivity for detection of B. glumae and B. gladioli separately in monoplex PCR or simultaneously in duplex PCR from both extracted gDNA and directly preheated bacterial cell suspensions. Limit of detection was as low as 0.1 ng of gDNA of both species and $3.86{\times}10^2cells$ for B. glumae and $5.85{\times}10^2cells$ for B. gladioli. On inoculated rice seeds, the designed primers could separately or simultaneously detect B. glumae and B. gladioli with a detection limit as low as $1.86{\times}10^3cells$ per rice seed for B. glumae and $1.04{\times}10^4cells$ per rice seed of B. gladioli. The novel primers maybe valuable as a more sensitive, specific, and robust tool for the efficient simultaneous detection of B. glumae and B. gladioli on rice seeds, which is important in combating rice panicle blight and seed rot by early detection and confirmation of the dissemination of pathogen-free rice seeds.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.12
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• pp.38-44
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• 2019

Various automation studies have been conducted to detect defective products based on product images. In the case of machine vision-based studies, size and color error are detected through a preprocessing process. A situation may arise in which the main features are removed during the preprocessing process, thereby decreasing the accuracy. In addition, complex systems are required to detect various kinds of defects. In this study, we designed and developed a system to detect errors by analyzing various conditions of defective products. We designed the deep learning algorithm to detect the defective features from the product images during the automation process using a convolution neural network (CNN) and verified the performance by applying the algorithm to the checker-switch failure detection system. It was confirmed that all seven error characteristics were detected accurately, and it is expected that it will show excellent performance when applied to automation systems for error detection.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1780-1787
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• 2014

Arterial oxygen saturation ($SpO_2$) monitoring for newborns requires special attention in neonatal intensive care units (NICUs). Newborns have very low photo-plethysmogram (PPG) amplitudes and their body movements are difficult to contain. Hardware design and its associated signal processing algorithms should be robust enough so that faulty measurements can be avoided. In this study, improved designs were implemented to deal with low perfusion, motion artifact, and the influence of ambient light. Dynamic range was increased by using different LED intensities and a feedback system. To minimize the effects of motion artifact and to discard other unqualified data, four additional algorithms were used, which were based on dual-trace detection, continuity of DC level, morphology of PPG, and simultaneity check of $SpO_2$. Our $SpO_2$ system was tested with newborns with normal respiration in the NICU. Our system provided fast, real-time responses and 100% artifact detection was accomplished under 84% of $SpO_2$.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.45-51
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• 2013

In this paper, the combination of ultraviolet and infrared sensors based design for flame signal detection algorithms was proposed with the application of light-wavelength from burning. And, the performance result of image detection was compared by an ultraviolet sensor, an infrared sensor, and the proposed dual-mode sensors(combination of ultraviolet and infrared sensors).

• Current Optics and Photonics
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• v.2 no.2
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• pp.134-139
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• 2018

A novel approach for frequency-tripling vector signal generation via balanced detection without precoding and optical filter is proposed. The scheme is mainly utilizing an integrated dual-polarization quadrature phase shift keying (DPQPSK) modulator. In the DPQPSK modulator, one QPSK modulator is driven by an RF signal to generate high-order optical sidebands, while the other QPSK modulator is modulated by I/Q data streams to produce baseband vector signal as an optical carrier. After that, a frequency-tripling 16-quadrature-amplitude-modulation (16QAM) vector millimeter-wave (mm-wave) signal can be obtained by balanced detection. The proposed scheme can reduce the complexity of transmitter digital signal processing. The results show that, a 4 Gbaud baseband 16QAM vector signal can be generated at 30 GHz by frequency-tripling. After 10 km single-mode fiber (SMF) transmission, the constellation and eye diagrams of the generated vector signal perform well and a bit-error-rate (BER) below than 1e-3 can be achieved.