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http://dx.doi.org/10.12989/sss.2018.22.2.239

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)
Publication Information
Smart Structures and Systems / v.22, no.2, 2018 , pp. 239-247 More about this Journal
Abstract
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.
Keywords
magnetic flux leakage; steel bar inspection; damage quantification; Hilbert transform; generalized extreme value distribution;
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Times Cited By KSCI : 3  (Citation Analysis)
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