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发布时间：2019-03-11

论文类型：会议论文

发表时间：2015-01-01

收录刊物：Scopus

摘要：Acoustic emission (AE) is an effective nondestructive method in recognizing the different types of damage occurring in composite structures. In this study AE technique was used for monitoring the carbon fiber-reinforced polymer (CFRP) confined circular concrete-filled steel tubular (CCFT) columns damage evolution. For during failure test various damage mechanisms appear, their classification is of major importance. Integration of k-means algorithm and fuzzy c-means methods was applied as an efficient clustering method to discriminate different failure modes. Damage properties of CFRP-CCFT columns were analyzed through AE signals. AE characteristic parameters were obtained through axial compression tests. Through clustering analysis, AE data can be classified into different types that related to different damage modes, the AE signals of obtained clusters were assigned to distinct damage mechanisms. Also, the dominance of damage mechanisms was determined based on the distribution of AE signals in different clusters. ? 2015, International Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII. All rights reserved.