Acoustic Emission Monitoring Of FRP-Confined Concrete Structure Under Reciprocating Load

FRP-confined circular concrete-filled steel tubular as a novel structural system, always used for major engineering structures, monitoring its full life safety is of great significance. Acoustic emission (AE) is a real-time and dynamic nondestructive technique, widely used in recognizing the damage evolution progress and failure modes of different materials. In this study damage property of glass fiber-reinforced polymer (GFRP) confined circular concrete-filled steel tubular (CCFT) columns under reciprocating load were investigated using acoustic emission signals. Primary research contents and results are as follows:On the basis of AE singals gathered during the failure process of GFRP-CCFT columns in reciprocating compression tests and low cyclic quasi-static tests, AE feature analysis is used to interpret the damage evolution process of GFRP-CCFT columns under different loading condition. Damage evolution process of GFRP-CCFT columns are divided into three stages, in accordance with the changes of cumulative AE features versus history curve of load, namely the elastic stage (?), the strengthen stage (?), and the failure stage (?).According to the conclusion of AE feature analysis, b-value analysis and RA-AF correlation analysis are introduced to evaluate the damage severity and failure modes of GFRP-CCFT columns under different loading condition. Provide reference information for the establishment of critical failure warning system for GFRP-CCFT structure.Fuzzy C-means clustering algorithm is conducted to identify the damage catagories of GFRP-CCFT columns under different reciprocating load, typical AE features of different damages are extracted for statistical analysis. Thus, damage catagories appeared during the failure process of GFRP-CCFT columns under reciprocating load can be effectively identified.Typical AE waveforms during the failure process of GFRP-CCFT columns are selected based on the clustering outcomes, different AE damage waveform is decomposed into varied frequency bands by wavelet transformation. To remove the effects of ambient noise, reasonably determined reconstruction coefficient is used for the reconstruction of AE damage signal, and faster fourier transform (FFT) is performed to accomplish the spectrum snalysis of various types of AE damage signal.