• 제목/요약/키워드: Detection Process

검색결과 3,672건 처리시간 0.039초

비동기 설비 신호 상황에서의 강건한 공정 이상 감지 시스템 연구 (Robust Process Fault Detection System Under Asynchronous Time Series Data Situation)

  • 고종명;최자영;김창욱;선상준;이승준
    • 산업공학
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    • 제20권3호
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    • pp.288-297
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    • 2007
  • Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

멀티 코어 프로세서 기반의 영상 감시 시스템을 위한 침입 탐지 처리의 가속화 (Acceleration of Intrusion Detection for Multi-core Video Surveillance Systems)

  • 이길범;정상진;김태환;이명진
    • 전자공학회논문지
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    • 제50권12호
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    • pp.141-149
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    • 2013
  • 본 논문은 멀티 코어 프로세서 기반의 영상 감시 시스템을 위한 침입 탐지 처리의 가속화를 제안한다. 침입 탐지 처리의 가속화를 위해 병렬화를 진행하였고, 이를 위해 기존 침입 탐지 알고리즘을 분석하고 데이터 의존성을 고려하여 프레임 단위의 병렬화된 처리 구조를 설계하였다. 병렬화된 침입 탐지 처리의 유효성을 검증하기 위하여 다중 쓰레드 기반의 프로그램으로 구현하여 침입 탐지의 가속화 정도를 측정하였다. 구현한 침입 탐지 처리 프로그램의 탐지 속도는 논리적 쓰레드를 8개까지 구현할 수 있는 환경에서 기존 단일 쓰레드 처리 대비 최대 353.76%가 향상되었다.

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.

DNA 검출 공정 전용 플라스틱 튜브형 시험관 개발에 관한 연구 (A study on development of plastic vial tube for the DNA detection process)

  • 최규완;라문우;강정희;장성호
    • Design & Manufacturing
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    • 제11권3호
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    • pp.35-40
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    • 2017
  • PCR(Polymerase chain reaction) is a technique to replicate and amplify a desired part of DNA. It is used in various aspects such as DNA fingerprint analysis and rare DNA amplification of an extinct animal. Especially in the medical diagnosis field, it provides various measurement methods at the molecular level such as genetic diagnosis, and is a basic tool for molecular diagnostics. The internal shape of the plastic vial tube for PCR analysis used in the DNA detection process, and the surface roughness and internal cleanliness can affect detection and discrimination results. The plastic vial tube demanded by the developer of the PCR analysis equipment should be changed to a structure that eliminates the residual washing solution in the washing process to ensure the internal cleanliness. Thus the internal structure and the internal surface design for improving the PCR amplification efficiency are key issues to develop the plastic vial tube for the DNA detection process.

Out-Of-Domain Detection Using Hierarchical Dirichlet Process

  • Jeong, Young-Seob
    • 한국컴퓨터정보학회논문지
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    • 제23권1호
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    • pp.17-24
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    • 2018
  • With improvement of speech recognition and natural language processing, dialog systems are recently adapted to various service domains. It became possible to get desirable services by conversation through the dialog system, but it is still necessary to improve separate modules, such as domain detection, intention detection, named entity recognition, and out-of-domain detection, in order to achieve stable service offer. When it misclassifies an in-domain sentence of conversation as out-of-domain, it will result in poor customer satisfaction and finally lost business. As there have been relatively small number of studies related to the out-of-domain detection, in this paper, we introduce a new method using a hierarchical Dirichlet process and demonstrate the effectiveness of it by experimental results on Korean dataset.

SMD Detection and Classification Using YOLO Network Based on Robust Data Preprocessing and Augmentation Techniques

  • NDAYISHIMIYE, Fabrice;Lee, Joon Jae
    • Journal of Multimedia Information System
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    • 제8권4호
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    • pp.211-220
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    • 2021
  • The process of inspecting SMDs on the PCB boards improves the product quality, performance and reduces frequent issues in this field. However, undesirable scenarios such as assembly failure and device breakdown can occur sometime during the assembly process and result in costly losses and time-consuming. The detection of these components with a model based on deep learning may be effective to reduce some errors during the inspection in the manufacturing process. In this paper, YOLO models were used due to their high speed and good accuracy in classification and target detection. A SMD detection and classification method using YOLO networks based on robust data preprocessing and augmentation techniques to deal with various types of variation such as illumination and geometric changes is proposed. For 9 different components of data provided from a PCB manufacturer company, the experiment results show that YOLOv4 is better with fast detection and classification than YOLOv3.

플라즈마 식각공정에서의 EPD(End Point Detection) 제어기에 관한 연구 (A study on EPD(End Point Detection) controller on plasma teaching process)

  • 최순혁;차상엽;이종민;우광방
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.415-418
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    • 1996
  • Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.

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THE DEVELOPMENT OF CHANGE DETECTION SOFTWARE FOR PUBLIC SERVICES

  • Jeong, Soo;Lee, Sun-Gu;Kim, Youn-Soo;Kim, Yong-Seung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.702-705
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    • 2006
  • Change detection is a core function of remote sensing. It can be widely used in public services such as land monitoring, damage assessment from disaster, analysis of city growth, etc. However, it seems that the change detection using satellite imagery has not been fully used in public services. For the person who is in charge of public services, it seems not to be ease to implement the change detection because various functions are combined into it. So, to promote the use of the change detection in public services, the standard, the process and the method for the change detection in public services should be established. And the software which supports that will be very useful. This study aims to promote the use of satellite imagery in public services by building up the change detection process which are suitable for general public services and developing the change detection software to support the process. The software has been developed using ETRI Components for Satellite Image Processing to support the interoperability with other GIS software.

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독립성분분석을 이용한 다변량 공정에서의 고장탐지 방법 (Fault Detection Method for Multivariate Process using ICA)

  • 정승환;김민석;이한수;김종근;김성신
    • 한국정보통신학회논문지
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    • 제24권2호
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    • pp.192-197
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    • 2020
  • 대규모 발전소나 화학공정과 같은 다변량 공정은 매우 위험한 환경에서 운전되기 때문에 고장이 발생하면 심각한 인적·물적 손실이 발생할 수 있다. 따라서 시스템의 고장을 사전에 탐지할 수 있는 온라인 모니터링 기술이 필수적이다. 본 논문에서는 세 가지의 다른 다변량 공정 데이터에 ICA를 적용하여 고장탐지를 수행하였고, PCA와 성능을 비교하였다. ICA 기반의 고장탐지 절차는 크게 오프라인 과정과 온라인 과정으로 나뉜다. 오프라인 과정에서는 시스템이 정상일 때 계측된 데이터를 이용하여 고장판별을 위한 문턱 값을 설정한다. 그리고 온라인 과정에서는 실시간으로 계측되는 질의벡터에 대한 통계량을 계산한 후, 계산된 통계량과 사전에 정의된 문턱 값과 비교하여 고장을 판별한다. 본 논문에서 이용한 세 가지의 다변량 공정 데이터에 실험한 결과, ICA 기반 고장탐지 방법이 시스템의 고장을 사전에 탐지하였고, PCA 보다 우수한 고장탐지 성능을 보여주었다.

Collaborative Process to Facilitate BIM-based Clash Detection Tasks for Enhancing Constructability

  • Seo, Jung-Ho;Lee, Baek-Rae;Kim, Ju-Hyung;Kim, Jae-Jun
    • 한국건축시공학회지
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    • 제12권3호
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    • pp.299-314
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    • 2012
  • One of reasons for introducing Building Information Modeling (BIM) is to support clash detection tasks by means of a 3D product model. In the conventional construction project process, clashes have been found during construction phase. However, it can cause cost overrun and time delay. In order to investigate and correct clash detections at design phase, relevant business process and guide for this task should be provided. This study aims to identify hindrances in clash detection tasks at the design phase and analyze its current process using IDEF0 model. Despite the convenience of IDEF0 as a systems analysis tool, professional participants might have difficulties to understand their own tasks according to business process. For this reason, in this research, Business Process Model and Notation (BPMN) is introduced to provide ideal process and required decision making governance. The provide BPMN model will provide insights for a BIM-based collaborative environment to enhance the constructability through the construction project.