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    원격조종 콘크리트 표면절삭 장비를 위한 머신비전 기반 품질관리 시스템 = Machine Vision based Quality Management System for Tele-operated Concrete Surface Grinding Machine

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    https://www.riss.kr/link?id=A101662942

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Concrete surface grinding is frequently used for flatness of concrete surface, concrete pavement rehabilitation, and adhesiveness in pavement construction. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding highly depend on the skills of worker. Thus, the development of remote controlled concrete surface grinding equipment is necessary to prevent the environmental pollution and to protect the workers from hazardous work condition. However, it is difficult to evaluate the grinded surface objectively in a remote controlled system. Also, The machine vision system developed in this study takes the images of grinded surface with the network camera for image processing. Then, by representing the quality test results to the integrated program of the remote control station, the quality control system is constructed. The machine vision algorithm means the image processing algorithm of grinded concrete surface and this paper presents the objective quality control standard of grinded concrete surface through the application of the suggested algorithm.
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    Concrete surface grinding is frequently used for flatness of concrete surface, concrete pavement rehabilitation, and adhesiveness in pavement construction. The procedure is, however, labor intensive and has a hazardous work condition. Also, the produc...

    Concrete surface grinding is frequently used for flatness of concrete surface, concrete pavement rehabilitation, and adhesiveness in pavement construction. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding highly depend on the skills of worker. Thus, the development of remote controlled concrete surface grinding equipment is necessary to prevent the environmental pollution and to protect the workers from hazardous work condition. However, it is difficult to evaluate the grinded surface objectively in a remote controlled system. Also, The machine vision system developed in this study takes the images of grinded surface with the network camera for image processing. Then, by representing the quality test results to the integrated program of the remote control station, the quality control system is constructed. The machine vision algorithm means the image processing algorithm of grinded concrete surface and this paper presents the objective quality control standard of grinded concrete surface through the application of the suggested algorithm.

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    참고문헌 (Reference)

    1 이원식, "원격조종 콘크리트 표면절삭 장비의 프로토타입 개발에 관한 연구" 대한토목학회 27 (27): 741-748, 2007

    2 Oh, J. T, "Vehicle detection using video image processing system : Evaluation of PEEK Video Trak" ASCE 129 : 462-465, 2003

    3 Hryciw, D. R, "Soil image processing -single grains to particle assemblies" 1-6, 2006

    4 Haran, G. J, "Real-time image processing algorithms for the detection of road and environmental conditions" ASCE 55-60, 2006

    5 Leu, S, "Digital image processing based approach for tunnel excavation faces" 14 : 750-765, 2005

    6 Gonzalez, C. R, "Digital image processing" Pearson Education 595-611, 2002

    7 Lee, S, "Automated recognition of surface defects using digital color image processing" 15 : 540-549, 2006

    8 Yu, S, "Auto inspection system using a mobile robot for detecting concrete cracks in a tunnel" 16 : 255-261, 2007

    9 Nobuyuki Otsu, "A threshold selection method from gray level histograms" 9 (9): 62-66, 1975

    10 Woo, S, "A robotic system for road lane painting" 17 : 122-129, 2008

    1 이원식, "원격조종 콘크리트 표면절삭 장비의 프로토타입 개발에 관한 연구" 대한토목학회 27 (27): 741-748, 2007

    2 Oh, J. T, "Vehicle detection using video image processing system : Evaluation of PEEK Video Trak" ASCE 129 : 462-465, 2003

    3 Hryciw, D. R, "Soil image processing -single grains to particle assemblies" 1-6, 2006

    4 Haran, G. J, "Real-time image processing algorithms for the detection of road and environmental conditions" ASCE 55-60, 2006

    5 Leu, S, "Digital image processing based approach for tunnel excavation faces" 14 : 750-765, 2005

    6 Gonzalez, C. R, "Digital image processing" Pearson Education 595-611, 2002

    7 Lee, S, "Automated recognition of surface defects using digital color image processing" 15 : 540-549, 2006

    8 Yu, S, "Auto inspection system using a mobile robot for detecting concrete cracks in a tunnel" 16 : 255-261, 2007

    9 Nobuyuki Otsu, "A threshold selection method from gray level histograms" 9 (9): 62-66, 1975

    10 Woo, S, "A robotic system for road lane painting" 17 : 122-129, 2008

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2022 평가 계속평가 신청대상 (등재유지)
    2017-01-01 등재 우수등재학술지 선정 (계속평가)
    2013-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2010-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2008-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2006-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2004-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2001-07-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    1998-07-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.4 0.4 0.41
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.38 0.35 0.707 0.11
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