期刊
MATERIALS
卷 12, 期 18, 页码 -出版社
MDPI
DOI: 10.3390/ma12182894
关键词
magnetic flux leakage; wire rope non-destructive evaluation; damage type classification; signal-processing; support vector machine
类别
资金
- Basic Science Research Program through the National Research Foundation - Ministry of Education [2017R1A6A3A04011933, 2017R1A2B3007607]
- Ministry of Land, Infrastructure and Transport of the Korean government [18CTAP-C130209-02]
- National Research Foundation of Korea [2017R1A2B3007607, 2017R1A6A3A04011933] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Wire ropes used in various applications such as elevators and cranes to safely carry heavy weights are vulnerable to breakage or cross-sectional loss caused by the external environment. Such damage can pose a serious risk to the safety of the entire structure because damage under tensile force rapidly expands due to concentration of stress. In this study, the magnetic flux leakage (MFL) method was applied to diagnose cuts, corrosion, and compression damage in wire ropes. Magnetic flux signals were measured by scanning damaged wire rope specimens using a multi-channel sensor head and a compact data acquisition system. A series of signal-processing procedures, including the Hilbert transform-based enveloping process, was applied to reduce noise and improve the resolution of signals. The possibility of diagnosing several types of damage was verified using enveloped magnetic flux signals. The characteristics of the MFL signals according to each damage type were then analyzed by comparing the extracted damage indices for each damage type. For automated damage type classification, a support vector machine (SVM)-based classifier was trained using the extracted damage indices. Finally, damage types were automatically classified as cutting and other damages using the trained SVM classifier.
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