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- 저자 : Fangzhu Du (검색결과 3 건)
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Non-destructive evaluation and pattern recognition for SCRC columns using the AE technique
Du, Fangzhu,Li, Dongsheng Techno-Press 2019 Structural monitoring and maintenance Vol.6 No.3
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.
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Cluster analysis and damage identification for FRP/steel-confined RC column using AE technique
Fangzhu Du,Dongsheng Li,Dapeng Qiu 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.3
This article presents the damage evaluation and pattern recognition for the newly proposed fiber reinforced polymer (FRP)/steel-confined reinforced concrete columns. The interaction of FRP material, steel tube, and reinforced concrete lead to complex damage mechanisms and invisible damage modes. The prevailing acoustic emission (AE) technique was applied to monitor the damage process and detect the sheltered damages under cyclic loading. Characteristic AE parameters, such as energy and duration, were extracted to disclose the damage evolution and evaluate the damage state. Three typical damage stages were identified. The fuzzy C.means (FCM) algorithm and particle swarm optimization (PSO) algorithm were applied as efficient clustering tools to discriminate different damage signals of FRP/steel-confined RC columns. Five types of damage mechanisms were identified and illustrated based on the statistical analysis of typical AE features. Furthermore, typical damage waveforms were extracted, the frequency content of each damage signal was discussed on the basis of wavelet transform.
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Yanlei Wang,Dong-Sheng Li,Fangzhu Du,Zhi Chen 국제구조공학회 2016 Smart Structures and Systems, An International Jou Vol.18 No.3
The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.
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