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Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads
This paper aims to study the strength and damage characteristics of basalt fiber-reinforced concrete (BFRC) under dynamic splitting tensile loads. Brazilian disk splitting tests and acoustic emission (AE) tests were carried out on BFRC herein. The improvement effects of loading rate and fiber content on the dynamic splitting tensile strength of BFRC were studied. Then, AE wavelet analysis methods (wavelet energy spectrum coefficient and maximum wavelet energy value) were employed to analyze the AE signals generated by BFRC. Additionally, a back-propagation (BP) artificial neural network was established to identify the damage stage of BFRC under dynamic splitting tensile loads. The test results showed that the improvement effect of the loading rate on the dynamic splitting tensile strength was enhanced with an increasing loading rate, and the enhancing effect of basalt fiber in the cases of 0.1% or 0.15% fiber dosages was better than that of the others. Most of the AE signals generated by BFRC were low frequency. Furthermore, the loading rate and the addition of fibers had a considerable impact on the wavelet energy spectrum coefficients corresponding to different bands and the distribution of maximum wavelet energy values of BFRC. Finally, the recognition rate of this BP neural network increased with the increment of the number of AE samples with the progress of loading.
Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads
This paper aims to study the strength and damage characteristics of basalt fiber-reinforced concrete (BFRC) under dynamic splitting tensile loads. Brazilian disk splitting tests and acoustic emission (AE) tests were carried out on BFRC herein. The improvement effects of loading rate and fiber content on the dynamic splitting tensile strength of BFRC were studied. Then, AE wavelet analysis methods (wavelet energy spectrum coefficient and maximum wavelet energy value) were employed to analyze the AE signals generated by BFRC. Additionally, a back-propagation (BP) artificial neural network was established to identify the damage stage of BFRC under dynamic splitting tensile loads. The test results showed that the improvement effect of the loading rate on the dynamic splitting tensile strength was enhanced with an increasing loading rate, and the enhancing effect of basalt fiber in the cases of 0.1% or 0.15% fiber dosages was better than that of the others. Most of the AE signals generated by BFRC were low frequency. Furthermore, the loading rate and the addition of fibers had a considerable impact on the wavelet energy spectrum coefficients corresponding to different bands and the distribution of maximum wavelet energy values of BFRC. Finally, the recognition rate of this BP neural network increased with the increment of the number of AE samples with the progress of loading.
Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads
J. Mater. Civ. Eng.
Zhang, Hua (author) / Jin, Chuanjun (author) / Zhang, Xiaoyu (author) / Ji, Shanshan (author) / Liu, Xinyue (author) / Li, Xuechen (author)
2023-06-01
Article (Journal)
Electronic Resource
English
Splitting Cracks in Reinforced Concrete Elements under Tensile Loads
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