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    RISS 인기검색어

      KCI등재 SCOPUS

      차세대 고속열차의 레일표면 결함 검출 시스템

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      다국어 초록 (Multilingual Abstract)

      In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.
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      In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as ...

      In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.

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      목차 (Table of Contents)

      • Abstract
      • 1. 서론
      • 2. 레일표면 결함 검출 시스템
      • 3. 시험 결과 및 고찰
      • 4. 결론
      • Abstract
      • 1. 서론
      • 2. 레일표면 결함 검출 시스템
      • 3. 시험 결과 및 고찰
      • 4. 결론
      • References
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      참고문헌 (Reference)

      1 G. Sivaram, "Sparse multilayer perceptron for phoneme recognition" 20 (20): 23-29, 2012

      2 G. E. Hinton, "Reducing the dimensionality of data with neural networks" 313 (313): 504-507, 2006

      3 L. Jie, "Real-time rail head surface defect detection:A geometrical approach" 5 (5): 769-774, 2009

      4 R. J. Hill, "Rail track distributed transmission line impedance and admittance: theoretical modeling and experimental results" 42 (42): 225-241, 1993

      5 V. N. Ghate, "Optimal MLP neural network classifier for fault detection of three phase induction motor" 37 (37): 3468-3481, 2010

      6 C. M. Bishop, "Neural Networks for Pattern Recognition" Oxford university Press 1995

      7 Z. Liu, "Inspection of rail surface defects based on image processing" 1 : 472-475, 2010

      8 Z. Zhang, "Feature-Based Facial Expression Recognition:Sensitivity Analysis and Experiments with a Multilayer Perceptron" 13 (13): 893-911, 1999

      9 J. Chen, "Fault detection and diagnosis for railway track circuits using neurofuzzy systems" 16 (16): 585-596, 2008

      10 A. Debiolles, "Combined use of Partial Least Squares regression and neural network for diagnosis tasks" 2004

      1 G. Sivaram, "Sparse multilayer perceptron for phoneme recognition" 20 (20): 23-29, 2012

      2 G. E. Hinton, "Reducing the dimensionality of data with neural networks" 313 (313): 504-507, 2006

      3 L. Jie, "Real-time rail head surface defect detection:A geometrical approach" 5 (5): 769-774, 2009

      4 R. J. Hill, "Rail track distributed transmission line impedance and admittance: theoretical modeling and experimental results" 42 (42): 225-241, 1993

      5 V. N. Ghate, "Optimal MLP neural network classifier for fault detection of three phase induction motor" 37 (37): 3468-3481, 2010

      6 C. M. Bishop, "Neural Networks for Pattern Recognition" Oxford university Press 1995

      7 Z. Liu, "Inspection of rail surface defects based on image processing" 1 : 472-475, 2010

      8 Z. Zhang, "Feature-Based Facial Expression Recognition:Sensitivity Analysis and Experiments with a Multilayer Perceptron" 13 (13): 893-911, 1999

      9 J. Chen, "Fault detection and diagnosis for railway track circuits using neurofuzzy systems" 16 (16): 585-596, 2008

      10 A. Debiolles, "Combined use of Partial Least Squares regression and neural network for diagnosis tasks" 2004

      11 J. Korbicz, "Advances in fault diagnosis systems" 725-733, 2004

      12 S. H. Ryu, "A Study on Overall Measurement System Development of HEMU-400X" 14 (14): 484-488, 2011

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      공동연구자 (7)

      유사연구자 (20) 활용도상위20명

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 학술지 통합 (기타) KCI등재
      2001-01-01 평가 등재학술지 유지 (등재유지) KCI등재
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.27 0.27 0.24
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.21 0.19 0.366 0.08
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