Damage properties of carbon fiber-reinforced polymer (CFRP) confined circular concrete-filled steel tubular (CCFT) columns were analyzed through acoustic emission (AE) signals. AE characteristic parameters were obtained through axial compression tests. The severity of damage to CFRP-CCFT columns was estimated using the growing trend of AE accumulated energy as basis. The bearing capacity of CFRP-CCFT columns and AE accumulated energy improved as CFRP layers increased. The damage process was studied using a number of crucial AE parameters. The cracks’ mode can be differentiated through the ratio of the rise time to the waveform amplitude and through average frequency analysis. With the use of intensity signal analysis, the damage process of the CFRP-CCFT columns can be classified into three levels that represent different degrees. Based on b-value analysis, the development of the obtained cracks can be defined. Thus, identifying an initial yielding and providing early warning is possible.

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Abstract" novel beamforming array technique and probability-based diagnostic imaging method are proposed to determine the acoustic emission "E source in plate-like structures. The technique that differs from common beamforming array techniques, in particular a sensor network, is used instead of a linear sensor array, to highlight information on the "E source location in one coordinate system as energy distribution. To reduce the uncertainty, avoid the boundary reflection effect, and ensure the rationality of the signal superposition, a Hilbert transform-based signal processing is applied before the delay-and-sum algorithm and a probability-based diagnostic imaging method is developed for "E source localization. The finite element numerical simulation method and the pencil-lead-broken experiment on aluminum plate are also conducted, and a thin-walled cylinder pipe-like structure is also tested by the pencil-lead-broken experiment to develop the application of the proposed method in various fields. The results indicate that this method is efficient and capable of visually showing the localization results highlighted in the probability images.

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