• 한국인터넷방송통신학회논문지
• /
• 제22권4호
• /
• pp.119-125
• /
• 2022

소형 대공 추적레이다용 전원공급기는 시스템이 잡음의 영향 없이 빠르고 안정적으로 전원을 공급받을 수 있도록 해야 한다. 이를 위하여 신뢰성 있는 전원변환을 위하여 DC-DC 변환기를 많이 적용한다. 또한 DC-DC 변환기의 스위칭 주파수 노이즈가 시스템의 탐지 추적 성능에 영향을 줄 수 있는 False Alarm 과 Ghost 를 유발하지 않도록 해야 하며, 추적 레이다가 동작중 실시간으로 전원을 모니터링 할 수 있는 점검 기능을 보유하고 있어야 한다. 본 연구에서는 소형 대공 추적 레이다에 적용하기 위하여 +28VDC 입력을 받아서 최대 출력 𐩒𐩒𐩒 W, 효율 80% 이상(@100%부하), 출력 전원 6개의 다중 출력 스위칭 전원공급기를 개발하였고 효율 80% 이상을 달성하기 위하여 전력이 큰 출력에 대해서는 DC-DC 변환기를 적용하였고 나머지 소전력 출력에 대해서는 출력 전류 및 노이즈를 고려하여 리니어 레귤레이터를 적용하여 설계 제작하여 시험 결과 100% 부하조건에서 85%의 우수한 효율 특성을 확인하였다.

• 천문학회보
• /
• 제40권1호
• /
• pp.56.2-56.2
• /
• 2015

The KMTNet Supernovae Project utilizes the large $2^{\circ}{\times}2^{\circ}$ field of view of the three KMTNet telescopes to search and monitor supernovae, especially early ones, and other optical transients. A key component of the project is to build a data pipeline with a descent latency and an early alerting system that can handle the large volume of the data in an efficient and a prompt way, while minimizing false alarms, which casts a significant challenge to the software development. Here we present the current status of their development. The pipeline utilizes a difference image analysis technique to discover candidate transient sources after making correction of image distortion. In the early phase of the program, final selection of transient sources from candidates will mainly rely on multi-filter, multi-epoch and multi-site screening as well as human inspection, and an interactive web-based system is being developed for this purpose. Eventually, machine learning algorithms, based on the training set collected in the early phase, will be used to select true transient sources from candidates.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권11호
• /
• pp.2720-2736
• /
• 2013

Multi-view face detection has become an active area for research in the last few years. In this paper, a novel multi-view human face detection algorithm based on improved real Adaboost is presented. Real Adaboost algorithm is improved by weighted combination of weak classifiers and the approximately best combination coefficients are obtained. After that, we proved that the function of sample weight adjusting method and weak classifier training method is to guarantee the independence of weak classifiers. A coarse-to-fine hierarchical face detector combining the high efficiency of Haar feature with pose estimation phase based on our real Adaboost algorithm is proposed. This algorithm reduces training time cost greatly compared with classical real Adaboost algorithm. In addition, it speeds up strong classifier converging and reduces the number of weak classifiers. For frontal face detection, the experiments on MIT+CMU frontal face test set result a 96.4% correct rate with 528 false alarms; for multi-view face in real time test set result a 94.7 % correct rate. The experimental results verified the effectiveness of the proposed approach.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제37권8호
• /
• pp.647-652
• /
• 2010

Esterel이라는 절차형(imperative) 동기(synchronous) 언어로부터 회로를 합성(synthesis)할 때, 하나의 동기장치(synchronizer)가 한 클럭에 중복사용되는 문제(schizophrenic parallel synchronizer)가 발생할 수 있다. 기존 컴파일러는 동기장치가 중복사용될 경우 동기장치를 복제하여 이 문제를 해결하고 있다. 본 논문은 동기장치가 중복사용되더라도 회로상/기능상 문제가 없는 조건을 제시하고, 이를 기반으로 소스코드를 분석하여 복제해야만 하는 동기장치를 찾아주는 알고리즘을 제안한다. 이 알고리즘은 컴파일러가 중복사용되는 동기장치들 중에서 꼭 복제해야만 하는 것을 알 수 있게 해 주어, Esterel 프로그램을 좀 더 작은 회로로 합성할 수 있도록 한다.

• 한국소음진동공학회논문집
• /
• 제27권2호
• /
• pp.148-154
• /
• 2017

This paper discussed design for resonance avoidance of sensor plates of loose-parts monitoring systems (LPMS) in nuclear power plants (NPP). An LPMS monitors impact of loose parts in primary loop of NPP by using accelerometers, which is mounted on sensor plates. Resonance of the plates may cause false alarms at frequencies over 10 kHz, which can be misunderstood as impact signals of loose parts with small mass and cause unnecessary response of NPP operators. Modal analysis was carried out for the existing sensor plate and design parameters affecting natural frequencies were chosen. Frequency response functions of plates were analyzed by changing the parameters and the optimized plate design for avoiding resonance was determined. Experiments was carried out for the plate specimen with improved design and verified the proposed approach and design.

• Structural Monitoring and Maintenance
• /
• 제5권1호
• /
• pp.51-65
• /
• 2018

A number of sensing techniques have been implemented for detecting defects in civil infrastructures instead of onsite human inspections in structural health monitoring. However, the issue of faults in sensors has not received much attention. This issue may lead to incorrect interpretation of data and false alarms. To overcome these challenges, this article presents a deep learning-based method with a new architecture of Stateful Long Short Term Memory Neural Networks (S-LSTM NN) for detecting sensor fault without going into details of the fault features. As LSTMs are capable of learning data features automatically, and the proposed method works without an accurate mathematical model. The detection of four types of sensor faults are studied in this paper. Non-stationary acceleration responses of a three-span continuous bridge when under operational conditions are studied. A deep network model is applied to the measured bridge data with estimation to detect the sensor fault. Another set of sensor output data is used to supervise the network parameters and backpropagation algorithm to fine tune the parameters to establish a deep self-coding network model. The response residuals between the true value and the predicted value of the deep S-LSTM network was statistically analyzed to determine the fault threshold of sensor. Experimental study with a cable-stayed bridge further indicated that the proposed method is robust in the detection of the sensor fault.

• 한국위성정보통신학회논문지
• /
• 제10권2호
• /
• pp.70-74
• /
• 2015

본 논문은 위성통신 기반의 위성 영상감시 센서 네트워크 적용을 위한 스마트 비젼 센서에 대해 기술한다. 스마트 비젼센서 단말은 현장에서 산불, 연기, 침입자 움직임 등의 이벤트를 자동감지하면서 높은 성능 신뢰도, 견고한 하드웨어 내구성, 용이한 유지보수, 끊김없는 통신유지 기능들이 요구된다. 이러한 요구사항들을 만족시키기 위하여 스마트 비젼 센서가 내장된 초소형 위성통신 단말을 제안하며 위성 송수신 기능과 더불어 고 신뢰도의 임베디드 영상분석 및 영상압축 기능을 처리한다. 제안하는 비젼 센서 알고리즘의 컴퓨터 시뮬레이션과 비젼 센서 시제품 시험을 통하여 영상감시 성능을 검증하였으며 실용성을 확인하였다.

• 천문학회지
• /
• 제47권6호
• /
• pp.209-214
• /
• 2014

In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.

• Smart Structures and Systems
• /
• 제22권2호
• /
• pp.201-207
• /
• 2018

This paper proposes a line laser thermography scanning (LLTS) system for multiple crack evaluation on a concrete structure, as the core technology for unmanned aerial vehicle-mounted crack inspection. The LLTS system consists of a line shape continuous-wave laser source, an infrared (IR) camera, a control computer and a scanning jig. The line laser generates thermal waves on a target concrete structure, and the IR camera simultaneously measures the corresponding thermal responses. By spatially scanning the LLTS system along a target concrete structure, multiple cracks even in a large scale concrete structure can be effectively visualized and evaluated. Since raw IR data obtained by scanning the LLTS system, however, includes timely- and spatially-varying IR images due to the limited field of view (FOV) of the LLTS system, a novel time-spatial-integrated (TSI) coordinate transform algorithm is developed for precise crack evaluation in a static condition. The proposed system has the following technical advantages: (1) the thermal wave propagation is effectively induced on a concrete structure with low thermal conductivity of approximately 0.8 W/m K; (2) the limited FOV issues can be solved by the TSI coordinate transform; and (3) multiple cracks are able to be visualized and evaluated by normalizing the responses based on phase mapping and spatial derivative processes. The proposed LLTS system is experimentally validated using a concrete specimen with various cracks. The experimental results reveal that the LLTS system successfully visualizes and evaluates multiple cracks without false alarms.

• 전자공학회논문지SC
• /
• 제41권4호
• /
• pp.13-20
• /
• 2004

본 논문에서는 표적 추적에 널리 사용되는 다중 가설 추적(MHT: Multiple Hypothesis Tracking) 알고리듬의 추적 성능을 예측할 수 있는 방법을 제시한다. MHT 알고리듬은 최적의 베이시안 필터로서, 측정된 데이터를 기초로 가능한 가설들을 구성하고, 각 가설들의 확률을 구하게 된다. 모든 측정치들은 관심 있는 실제 표적에서 기인할 수 있을 뿐만 아니라, 새로운 표적이거나 표적이외의 거짓에서 발생할 수도 있다는 사건을 고려하고 있기 때문에 다른 여러 추적 필터에 비해 MHT 알고리듬은 우수한 추적성능을 가지고 있다고 알려져 있다. 측정 데이터와 무관하게 추적기의 성능을 표현하기 위해서 HYCA(Hybrid Conditional Average)방법을 이용하여 MHT 알고리듬에서 발생하는 모든 가설 확률의 기대 값을 구한 후, 이를 이용하여 성능을 예측하는 방법을 제시한다. 수치실험을 통하여 이 논문에서 제시한 성능 예측이 타당함을 보인다.