Smart Structures and Systems

  • 제22권2호
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  • Pages.239-247
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  • 2018
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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Improvement of MFL sensing-based damage detection and quantification for steel bar NDE

  • Kim, Ju-Won (School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University) ;
  • Park, Minsu (Department of Civil & Environmental System Engineering, Sungkyunkwan University) ;
  • Kim, Junkyeong (Department of Civil & Environmental System Engineering, Sungkyunkwan University) ;
  • Park, Seunghee (School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University)
  • 투고 : 2017.05.20
  • 심사 : 2017.11.28
  • 발행 : 2018.08.25
⟨ 이전 논문 다음 논문 ⟩

초록

A magnetic flux leakage (MFL) method was applied to detect and quantify defects in a steel bar. A multi-channel MFL sensor head was fabricated using Hall sensors and magnetization yokes with permanent magnets. The MFL sensor head scanned a damaged specimen with five levels of defects to measure the magnetic flux density. A series of signal processing procedures, including an enveloping process based on the Hilbert transform, was performed to clarify the flux leakage signal. The objective damage detection of the enveloped signals was then analyzed by comparing them to a threshold value. To quantitatively analyze the MFL signal according to the damage level, five kinds of damage indices based on the relationship between the enveloped MFL signal and the threshold value were applied. Using the proposed damage indices and the general damage index for the MFL method, the detected MFL signals were quantified and analyzed relative to the magnitude of the damage increase.

키워드

과제정보

연구 과제 주관 기관 : National Research Foundation of Korea (NRF), Ministry of Land, Infrastructure, and Transport

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피인용 문헌

  1. 누설자속 기반 강판 두께별 국부 손상 진단 감도 분석 vol.11, pp.2, 2018, https://doi.org/10.21729/ksds.2018.11.2.53
  2. MFL-Based Local Damage Diagnosis and SVM-Based Damage Type Classification for Wire Rope NDE vol.12, pp.18, 2019, https://doi.org/10.3390/ma12182894
  3. 강구조물 진단을 위한 누설자속 기반 강판 손상의 이미지화 vol.23, pp.7, 2018, https://doi.org/10.11112/jksmi.2019.23.7.129