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http://dx.doi.org/10.12989/smm.2019.6.3.173

Non-destructive evaluation and pattern recognition for SCRC columns using the AE technique  

Du, Fangzhu (School of Civil Engineering, Dalian University of Technology)
Li, Dongsheng (School of Civil Engineering, Dalian University of Technology)
Publication Information
Structural Monitoring and Maintenance / v.6, no.3, 2019 , pp. 173-190 More about this Journal
Abstract
Steel-confined reinforced concrete (SCRC) columns feature highly complex and invisible mechanisms that make damage evaluation and pattern recognition difficult. In the present article, the prevailing acoustic emission (AE) technique was applied to monitor and evaluate the damage process of steel-confined RC columns in a quasi-static test. AE energy-based indicators, such as index of damage and relax ratio, were proposed to trace the damage progress and quantitatively evaluate the damage state. The fuzzy C-means algorithm successfully discriminated the AE data of different patterns, validity analysis guaranteed cluster accuracy, and principal component analysis simplified the datasets. A detailed statistical investigation on typical AE features was conducted to relate the clustered AE signals to micro mechanisms and the observed damage patterns, and differences between steel-confined and unconfined RC columns were compared and illustrated.
Keywords
steel-confined RC structure; acoustic emission; damage evaluation; cluster analysis; pattern recognition;
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