24 April 2020Corrosion-induced damage detection and conditional assessment for metallic civil structures using machine learning approaches (Conference Presentation)
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corrosion still responds for huge maintenance cost of nationwide civil structures. In this study, we explored a machine learning approach to extract information from sensory data for early-age corrosion-induced damage identification and classification. Lamb-wave guided signals of steel samples collected from simulated corrosion damage were used for model training and calibration. The results showed that the machine learning method allowed effective information fusion for early-age corrosion.
Zhibin Lin,Hong Pan,Zi Zhang,Fujian Tang, andXingyu Wang
"Corrosion-induced damage detection and conditional assessment for metallic civil structures using machine learning approaches (Conference Presentation)", Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 113792F (24 April 2020); https://doi.org/10.1117/12.2560131
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Zhibin Lin, Hong Pan, Zi Zhang, Fujian Tang, Xingyu Wang, "Corrosion-induced damage detection and conditional assessment for metallic civil structures using machine learning approaches (Conference Presentation)," Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 113792F (24 April 2020); https://doi.org/10.1117/12.2560131