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${\alpha}{\beta}$ 필터 및 NNPDA 알고리즘을 이용한 차량용 레이더 표적 추적 시스템 설계
배준형,현유진,이종훈,Bae, JunHyung,Hyun, EuGin,Lee, Jong-Hun 대한임베디드공학회 2011 대한임베디드공학회논문지 Vol.6 No.1
Automotive Radar Systems are currently under development for various applications to increase accuracy and reliability. The target tracking is most important in single or multiple target environments for accuracy. The tracking algorithm provides smoothed and predicted data for target position and velocity(Doppler). To this end, the fixed gain filter(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter) and dynamic filter(Kalman filter, Singer-Kalman filter, etc) are commonly used. Gating is used to decide whether an observation is assigned to an existing track or new track. Gating algorithms are normally based on computing a statistical error distance between an observation and prediction. The data association takes the observation-to-track pairings that satisfied gating and determines which observation-to-track assignment will actually be made. For data association, NNPDA(Nearest Neighbor Probabilistic Data Association) algorithm is proposed. In this paper, we designed a target tracking system developed for an Automotive Radar System. We show the experimental results of the 77GHz FMCW radar sensor on the roads. Four tracking algorithms(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter, 2nd order Kalman filter, Singer-Kalman filter) have been compared and analyzed to evaluate the performance in test scenario.
산업 시스템을 위한 고장 진단 및 고장 허용 제어 기술
배준형(Junhyung Bae) 한국전기전자학회 2021 전기전자학회논문지 Vol.25 No.3
본 논문에서는 산업 공정, 설비 및 모터 드라이브에 적용되는 고장 진단 및 고장 허용 제어 기술의 기본 개념, 접근법과 연구 동향에 대해서 개괄적으로 기술하였다. 산업 공정을 위한 고장 진단의 주요 역할은 공정의 결함 상태를 파악할 수 있는 효과적인 지표를 만든 후 고장이나 위험한 사고에 대해 적절한 조치를 취하는 것이다. 산업 공정에 패턴이 있는지 특정 프로세스 변수가 정상적으로 동작하는지 확인하기 위해 많은 고장 검출 및 진단 기법이 개발되었다. 먼저 본 논문에서는 데이터 기반 기법과 모델 기반 기법에 대하여 살펴본다. 두 번째로 산업 공정을 위한 고장 검출 및 진단 기법을 살펴본다. 세 번째로 수동형 및 능동형 고장 허용 제어 기법을 살펴본다. 마지막으로 AC 모터 드라이브에서 발생하는 주요 고장을 열거, 그 특성을 살펴보고 이를 위한 고장 진단 및 고장 허용 제어 기술을 살펴본다. This paper outlines the basic concepts, approaches and research trends of fault diagnosis and fault tolerant control applied to industrial processes, facilities, and motor drives. The main role of fault diagnosis for industrial processes is to create effective indicators to determine the defect status of the process and then take appropriate measures against failures or hazadous accidents. The technologies of fault detection and diagnosis have been developed to determine whether a process has a trend or pattern, or whether a particular process variable is functioning normally. Firstly, data-driven based and model-based techniques were described. Secondly, fault detection and diagnosis techniques for industrial processes are described. Thirdly, passive and active fault tolerant control techniques are considered. Finally, major faults occurring in AC motor drives were listed, described their characteristics and fault diagnosis and fault tolerant control techniques are outlined for this purpose.
고장 검출 필터를 사용한 항공기 터보팬 엔진 시스템의 고장 검출
배준형(Junhyung Bae) 한국전기전자학회 2021 전기전자학회논문지 Vol.25 No.2
하드웨어 이중화 구성 수를 줄이는 대표적인 방법은 마이크로컨트롤러로 고장을 검출, 식별 및 수용을 위한 해석적 기법으로 구현하는 것이다. 본 논문에서는 해석적 기법 중 하나인 고장 검출 필터를 항공기 터보팬 엔진 시스템에 적용하였다. 고장 검출 필터는 특수한 형태의 관측기로써 특정한 고장 발생시 잔차가 출력 공간에서 일정한 방향을 유지함으로써 고장의 위치 판별이 가능한 장점이 있다. 이에 본 논문에서는 터보팬 엔진 내 공기 터빈 시스템의 단일 입출력 동적 시스템 모델링, 고장 검출 필터 설계 및 이를 적용한 모의실험 결과를 나타내었다. 모의실험 결과를 통해 고장 검출 필터가 갖는 방향성에 대한 민감성 효과로 고장 검출이 유효하게 적용될 수 있음을 보였다. A typical way to reduce the number of hardware redundancy configurations is to implement them as analytical techniques for detecting, identifying and accepting failures with micro-controller. In this paper, one of the analytical techniques, the fault detection filter, is applied to aircraft turbofan engine system. The fault detection filter is a special type of observer that has the advantage of being able to determine the location of failures by maintaining a constant direction in the output space in the event of a particular failure. We present a single input/output dynamic system modeling of air turbine system in turbofan engine, a fault detection filter design, and simulation results applying it. Simulation results show that fault detection can be effectively applied as a sensitivity effect to the directionality of the detection filter.
배준형(Bae Junhyung),이상우(Lee Sangwoo),박태준(Park Taejoon),이동하(Lee Dong-Ha),강진규(Kang Jinkyu) 한국태양에너지학회 2012 한국태양에너지학회 학술대회논문집 Vol.2012 No.3
This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network; of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.
돌발상황에 따른 연령별 운전자 생리반응 비교를 위한 생체신호 추출, 선정 및 정량화
배준형(Junhyung Bae),원웅재(Woongjae Won),손준우(Joonwoo Son) 한국자동차공학회 2008 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
This paper is to collect young and older ages man driver's physiological signal under unexpected events and quantify physiological variables for diagnostic approach. The physiological signal is collected from driving simulator with measuring devices. The collected data were analyzed by the temporal pattern during simulated driving accident conditions. We investigated status a various physiological signals using autonomic nerve system such as PPG(peripheral plethysmograph), SCL(skin conductance level), SCR(skin conductance response), RSP(respiration), HR(heart rate). Three physiological signal with consistent pattern were selected and quantified in terms of slope and amplitude of the signal. The result of the paper can be used to design a system to monitor the driver's safety and health condition.