• 제목/요약/키워드: Simple detection process

검색결과 223건 처리시간 0.027초

고장벡터 모델링에 위한 프로세스 고장 검출필터의 설계 및 응용 (A Process Fault Detection Filter Design by Fault Vector Modelling Approach and an Application)

  • 이기상;배상욱
    • 대한전기학회논문지
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    • 제36권6호
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    • pp.430-436
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    • 1987
  • A Detection filter that can be used for the Detection and Isolation of process faults is proposed by the use of fault vector modelling, and is applied to DC Motor fault detection. The proposed detection filter is a new one in a view point that its outputs are the estimates of fault variables(or linear combination of them) while all the existing filters estimate the state of process. By this properties, the process fault detection systems with this filter can be constructed in very simple structure. Besides the simplicity of structure and design procedure, the filter has an useful feature that various types of fault can be estimated via the filter by choosing appropriate fault models.

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Pixel 군집화 Data를 이용한 실시간 반사광 검출 알고리즘 (Real-time Reflection Light Detection Algorithm using Pixel Clustering Data)

  • 황도경;안종우;강호선;이장명
    • 로봇학회논문지
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    • 제14권4호
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    • pp.301-310
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    • 2019
  • A new algorithm has been propose to detect the reflected light region as disturbances in a real-time vision system. There have been several attempts to detect existing reflected light region. The conventional mathematical approach requires a lot of complex processes so that it is not suitable for a real-time vision system. On the other hand, when a simple detection process has been applied, the reflected light region can not be detected accurately. Therefore, in order to detect reflected light region for a real-time vision system, the detection process requires a new algorithm that is as simple and accurate as possible. In order to extract the reflected light, the proposed algorithm has been adopted several filter equations and clustering processes in the HSI (Hue Saturation Intensity) color space. Also the proposed algorithm used the pre-defined reflected light data generated through the clustering processes to make the algorithm simple. To demonstrate the effectiveness of the proposed algorithm, several images with the reflected region have been used and the reflected regions are detected successfully.

딥러닝을 활용한 설비 이상 탐지 및 성능 분석 (Anomaly Detection and Performance Analysis using Deep Learning)

  • 황주효;진교홍
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.78-81
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    • 2021
  • 스마트공장 구축사업을 통해 제조업의 생산설비에 센서가 설치되고 각종 공정데이터를 실시간으로 수집할 수 있게 되었다. 이를 통해 제조공정의 설비이상으로 인한 생산중단을 줄이기 위해 실시간 설비 이상 탐지에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 생산설비의 이상탐지를 위해 제조데이터를 딥러닝 모델인 Autoencoder(AE), VAE(Variational Autoencoder), AAE(Adversarial Autoencoder)에 적용하여 그 결과를 도출하였다. 제조데이터는 단순 이동 평균 기법과 전처리 과정을 거쳐 입력데이터로 사용하였으며, 단순이동평균 기법의 윈도우 크기와 AE 모델의 특징벡터 크기에 따른 성능분석을 실시하였다.

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누설자속 탐상법 및 노이즈 필터를 이용한 와이어로프의 결함진단시스템 개발 (A Development of the Fault Detection System of Wire Rope using Magnetic Flux Leakage Inspection Method and Noise Filter)

  • 이영진;아미나;이권순
    • 전기학회논문지
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    • 제63권3호
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    • pp.418-424
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    • 2014
  • A large number of wire rope has been used in various industries such as cranes and elevators. When wire used for a long time, wire defects occur such as disconnection and wear. It leads to an accident and damage to life and property. To prevent this accident, we proposed a wire rope fault detection system in this paper. We constructed the whole system choosing the leakage fault detection method using hall sensors and the method is simple and easy maintenance characteristics. Fault diagnosis and analysis were available through analog filter and amplification process. The amplified signal is transmitted to the computer through the data acquisition system. This signal could be obtained improved results through the digital filter process.

공정고장 검출식별시스템을 위한 잔차발생기구 (A new residual generator for a Process FDIS)

  • 이기상;박태건;이상운
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 D
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    • pp.2014-2016
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    • 2003
  • A new residual generation scheme that can be employed in the process fault detection and isolation systems for linear (control) systems is suggested. The scheme is very simple, but provides the same information for the detection and isolation of the anticipated faults as the conventional multiple observer based schemes. Application results show the practical feasibility of the proposed scheme.

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미약한 시각 특징과 Haar 유사 특징들의 강화 연결에 의한 도로 상의 실 시간 차량 검출 (Real Time On-Road Vehicle Detection with Low-Level Visual Features and Boosted Cascade of Haar-Like Features)

  • 샴 아디카리;유현중;김형석
    • 제어로봇시스템학회논문지
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    • 제17권1호
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    • pp.17-21
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    • 2011
  • This paper presents a real- time detection of on-road succeeding vehicles based on low level edge features and a boosted cascade of Haar-like features. At first, the candidate vehicle location in an image is found by low level horizontal edge and symmetry characteristic of vehicle. Then a boosted cascade of the Haar-like features is applied to the initial hypothesized vehicle location to extract the refined vehicle location. The initial hypothesis generation using simple edge features speeds up the whole detection process and the application of a trained cascade on the hypothesized location increases the accuracy of the detection process. Experimental results on real world road scenario with processing speed of up to 27 frames per second for $720{\times}480$ pixel images are presented.

자기-바이어스 슈퍼 MOS 복합회로를 이용한 공정 검출회로 (A Process Detection Circuit using Self-biased Super MOS composit Circuit)

  • 서범수;조현묵
    • 융합신호처리학회논문지
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    • 제7권2호
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    • pp.81-86
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    • 2006
  • 본 논문에서는 새로운 개념의 공정 검출 회로를 제안하였다. 제안된 공정 검출 회로는 장채널 트랜지스터와 최소의 배선폭을 갖는 단채널 트랜지스터 사이의 공정변수의 차이를 비교한다. 이 회로는 공정 변이에 따라 발생하는 캐리어 이동도의 차이를 이용하여 이에 비례하는 차동 전류를 생성해 낸다. 이 방법에서는 고 이득 연산증폭기를 사용한 궤환 회로를 구현함으로써 두 개의 트랜지스터의 드레인 전압이 같아지도록 유지한다. 또한, 본 논문은 제안한 자기-바이어스 슈퍼 MOS 복합회로를 이용하여 고 이득 자기-바이어스 rail-to-rail 연산증폭기를 설계하는 새로운 방법을 소개한다. 설계된 연산증폭기의 이득은 단상의 $0.2V{\sim}1.6V$ 공통모드 범위에서 100dB 이상으로 측정되었다 최종적으로, 제안한 공정 검출 회로는 차동 VCO 회로에 직접 적용하였으며, 설계된 VCO 회로를 통해서 공정 검출 회로가 공정 코너들을 성공적으로 보상하고 광범위한 동작 영역에서 안정된 동작을 수행함을 확인할 수 있었다.

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PLC 디지털 제어 신호를 통한 LSTM기반의 이산 생산 공정의 실시간 고장 상태 감지 (Real-Time Fault Detection in Discrete Manufacturing Systems Via LSTM Model based on PLC Digital Control Signals)

  • 송용욱;백수정
    • 산업경영시스템학회지
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    • 제44권2호
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    • pp.115-123
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    • 2021
  • A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

SAR 자동표적인식 시스템에서의 탐지특징 결합 방법 개선 방안 (Improved Fusion Method of Detection Features in SAR ATR System)

  • 차민준;김형명
    • 한국군사과학기술학회지
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    • 제13권3호
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    • pp.461-469
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    • 2010
  • In this paper, we have proposed an improved fusion method of detection features which can enhance the detection probability under the given false alarm rate in the prescreening stage of SAR ATR(Synthetic Aperture Radar Automatic Target Recognition) system. Since the detection features have the positive correlation, the detection performance can be improved if the joint probability distribution of detection features is considered in the fusion process. The detection region is designed as a simple piecewise linear function which can be represented by few parameters. The parameters for the detection region can be derived by training the sample SAR images to maximize the detection probability with the given false alarm rate. Simulation result shows that the detection performance of the proposed method is improved for all combinations of detection features.

비젼 시스템을 이용한 2-D 원형 물체 추적 알고리즘의 비교에 관한 연구 (A Study on the Comparison of 2-D Circular Object Tracking Algorithm Using Vision System)

  • 한규범;김정훈;백윤수
    • 한국정밀공학회지
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    • 제16권7호
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    • pp.125-131
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    • 1999
  • In this paper, the algorithms which can track the two dimensional moving circular object using simple vision system are described. In order to track the moving object, the process of finding the object feature points - such as centroid of the object, corner points, area - is indispensable. With the assumption of two-dimensional circular moving object, the centroid of the circular object is computed from three points on the object circumference. Different kinds of algorithms for computing three edge points - simple x directional detection method, stick method. T-shape method are suggested. Through the computer simulation and experiments, three algorithms are compared from the viewpoint of detection accuracy and computational time efficiency.

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