• 제목/요약/키워드: False alarm

검색결과 604건 처리시간 0.026초

An Expert System For Fault Diagnosis Using Alarm Information

  • Park, Young-Moon;Ham, Wan-Kyun
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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    • pp.122-126
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    • 1988
  • This paper deals with an application of an expert system to transmission line fault diagnosis using alarm information line possible solution can be obtained even in case that the cause of alarms is due to relays, circuit breakers or alarm systems. The expert system diagnoses not only any possible fault element, but also normal or abnormal misoperations. Also, this system can give any possible answers only when the sum of appropriate error indices assigned to false operation of devices is less than the appropriate criterion specified in advance. This paper is written in Official Projection System-Version 5 (OPS-5) which is one of the AI languages.

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온사이트 지진조기경보를 위한 딥러닝 기반 실시간 오탐지 제거 (Deep Learning-Based, Real-Time, False-Pick Filter for an Onsite Earthquake Early Warning (EEW) System)

  • 서정범;이진구;이우동;이석태;이호준;전인찬;박남률
    • 한국지진공학회논문집
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    • 제25권2호
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    • pp.71-81
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    • 2021
  • This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

조사연구-공기흡입 화재탐지설비(ADS)에 대한 고찰

  • 류은열
    • 방재기술
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    • 통권19호
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    • pp.17-21
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    • 1995
  • This is to study installation standards of aspirating devices and detectors, which are components of ADS(aspirating fire detection system). The BFPSA(British Fire Protection System Association) code was mainly referred is studying. ADS aspirated air and smoke through the pipe and then checks if there is fire or not. It is now in the limelight because it can early alarm in case of fire and prevent false-alarming.

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여과기법 보안효율을 높이기 위한 센서네트워크 클러스터링 방법 (Enhancing Method to make Cluster for Filtering-based Sensor Networks)

  • 김병희;조대호
    • 한국정보통신설비학회:학술대회논문집
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    • 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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    • pp.141-145
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    • 2008
  • Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

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클러스터링 기반의 CR시스템에서 가중치 협력 스펙트럼 센싱 기술의 개선연구 (Improved Weighted-Collaborative Spectrum Sensing Scheme Using Clustering in the Cognitive Radio System)

  • 최규진;손성환;이주관;김재명
    • 한국ITS학회 논문지
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    • 제7권6호
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    • pp.101-109
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    • 2008
  • 본 논문은 클러스터링 기법을 도입하여 기존에 제안된 가중치 협력 스펙트럼 시스템에서 실질적으로 구하지 못했던 Pd를 구하고, 새로운 가중치 생성 알고리즘을 통하여 1차 사용자 신호의 감지 성능을 향상시키는 방법을 제안하였다. 유사한 채널을 같는 CR 사용자를 클러스터링 기법을 이용하여 그룹화하여 각각의 사용자로부터 획득한 센싱 결과를 토대로 Pd를 계산하였다. 또한, 각 클러스터의 검출확률의 제곱 합을 이용하여 가중치(Wj(n+1))를 생성하였다. 이는 기존의 방식보다 센싱 성능이 우수하였으며, 특히 1차 사용자의 신호가 갑자기 사라졌을 경우 신호가 없는 상황에서의 검출 확률인 false alarm rate가 낮아지는 결과를 보였다. 컴퓨터 모의실험을 통하여 이를 검증한다.

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Video smoke detection with block DNCNN and visual change image

  • Liu, Tong;Cheng, Jianghua;Yuan, Zhimin;Hua, Honghu;Zhao, Kangcheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권9호
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    • pp.3712-3729
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    • 2020
  • Smoke detection is helpful for early fire detection. With its large coverage area and low cost, vision-based smoke detection technology is the main research direction of outdoor smoke detection. We propose a two-stage smoke detection method combined with block Deep Normalization and Convolutional Neural Network (DNCNN) and visual change image. In the first stage, each suspected smoke region is detected from each frame of the images by using block DNCNN. According to the physical characteristics of smoke diffusion, a concept of visual change image is put forward in this paper, which is constructed by the video motion change state of the suspected smoke regions, and can describe the physical diffusion characteristics of smoke in the time and space domains. In the second stage, the Support Vector Machine (SVM) classifier is used to classify the Histogram of Oriented Gradients (HOG) features of visual change images of the suspected smoke regions, in this way to reduce the false alarm caused by the smoke-like objects such as cloud and fog. Simulation experiments are carried out on two public datasets of smoke. Results show that the accuracy and recall rate of smoke detection are high, and the false alarm rate is much lower than that of other comparison methods.

소나 위치 추정 성능 향상을 위한 LS기반 MRAL 후처리 기법 (MRAL Post Processing based on LS for Performance Improvement of Active Sonar Localization)

  • 장은정;한동석
    • 전자공학회논문지
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    • 제49권9호
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    • pp.172-180
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    • 2012
  • 수중 표적의 탐지를 위한 다중상태 소나에서 수신 신호는 많은 잔향 및 클러터 성분을 포함한다. 이는 표적탐지에서 오경보율을 높이는 주된 원인이다. MRAL(multiple return association and localization) 알고리듬은 수신신호를 위치적인 유사성을 기준으로 몇 개의 그룹으로 분류하고, 그룹의 수신신호들을 한 개의 반사체로부터 온 것으로 봄으로써 오경보율을 낮춘다. 그러나 그룹화로 인하여 MRAL 알고리듬의 결과로 나타나는 표적 및 클러터 등의 위치는 실제위치와 차이를 보일 수 있다. 본 논문에서는 MRAL 알고리듬의 출력으로서 나타나는 표적 및 클러터의 위치와 실제 표적 및 클러터의 위치와 차이를 줄이기 위하여, 후처리 기법으로 최소제곱법을 이용한 LS기반 MRAL 후처리 기법 알고리듬을 제안한다.

CFAR 검파기법을 이용한 주파수 영역 부분적응 어레이 알고리듬 (Frequency Domain Partially Adaptive Array Algorithm Combined with CFAR Technique)

  • 문성훈;한동석
    • 대한전자공학회논문지SP
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    • 제38권2호
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    • pp.227-236
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    • 2001
  • 본 논문에서는 주파수 영역 적응 어레이의 계산량을 감소시키기 위한 주파수 영역 부분적응 어레이 알고리듬인 센서링(censoring) 알고리듬을 제안하고, 이를 공간평활(spatial smoothing) 기법과 결합하여 공간평활로 인한 계산량 문제를 해결할 수 있는 센서링 공간평활 알고리듬을 제안한다. 제안한 센서링 알고리듬은 CFAR(constant false alarm rate) 검파기법을 이용하여 각 주파수 대역에 간섭신호가 있는지를 판단하고 간섭신호가 있는 주파수 대역의 해당 가중치에 대해서만 적응 알고리듬을 적용한다. 모의실험을 통하여 제안한 알고리듬을 사용한 GSC(generalized sidelobe canceller)가 기존의 주파수 영역 LMS(least mean square) 알고리듬을 사용한 GSC에 비하여 크게 줄어든 계산량으로 빠르게 간섭신호를 제거함을 확인하였다.

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카메라영상에 의한 DGPS-GIS기반 차선변경 지원시스템의 평가 및 신뢰성 검증 (Assessment and Reliability Validation of Lane Departure Assistance System Based on DGPS-GIS Using Camera Vision)

  • 문상찬;이순걸;김민우;주다니
    • 한국자동차공학회논문집
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    • 제22권6호
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    • pp.49-58
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    • 2014
  • This paper proposes a new assessment and reliability validation method of Lane Departure Assistance System based on DGPS-GIS by measuring lanes with camera vision. Assessment of lane departure is performed with yaw speed measurement and determination method for false alarm of ISO 17361 and performance validation is executed after generating departure warning boundary line by considering deviation error of LDAS using DGPS. Distance between the wheel and the lane is obtained through line abstraction using Hough transformation of the lane image with camera vision. Evaluation validation is obtained by comparing this value with the distance obtained with LDAS. The experimental result shows that the error of the extracted distance of the LDAS is within 5 cm. Also it proves performance of LDAS based on DGPS-GIS and assures effectiveness of the proposed validation method for system reliability using camera vision.

Tracking Capability Analysis of ARGO-M Satellite Laser Ranging System for STSAT-2 and KOMPSAT-5

  • Lim, Hyung-Chul;Seo, Yoon-Kyung;Na, Ja-Kyung;Bang, Seong-Cheol;Lee, Jin-Young;Cho, Jung-Hyun;Park, Jang-Hyun;Park, Jong-Uk
    • Journal of Astronomy and Space Sciences
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    • 제27권3호
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    • pp.245-252
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    • 2010
  • Korea Astronomy and Space Science Institute (KASI) has developed a mobile satellite laser ranging (SLR) system called ARGO-M since 2008 for space geodesy research and precise orbit determination technologies using SLR with mm level accuracy. ARGO-M is capable of night tracking and daylight tracking for which requires spatial, spectral and time filters due to high background noises. In this study, characteristics and specifications of ARGO-M are discussed and its tracking capabilities of night and daylight tracking are analyzed for STSAT-2B and KOMPSAT-5 through link budget. Additionally false alarm and signal detection probabilities are also analyzed depending on spectral and time filters for daylight tracking for these satellites.