Acoustic emission wavelet time-frequency characteristics of fiber reinforced mortar failure process under axial compression-Reference-Cited by-同舟云学术

Acoustic emission wavelet time-frequency characteristics of fiber reinforced mortar failure process under axial compression

Published:2023-05-01 Issue:5 Volume:65 Page:774-786
ISSN:0025-5300
Container-title:Materials Testing
language:en
Short-container-title:

Author:

Wang Yan¹,Wang Na²,Yan Chao²,Zhao Haitao²

Affiliation:

1. Hohai University , Nanjing 210024 , China

2. Hohai University , Nanjing , Jiangsu , China

Abstract

Abstract In order to investigate the wavelet time-frequency characteristics of fiber reinforced mortar under axial compression, acoustic emission signals associated with steel fiber reinforced mortar and polypropylene fiber reinforced mortar with five different fiber contents (0 to 2.0 vol%) under axial compression were recorded. A new method of multivariate statistical analysis of wavelet time-frequency maps based on Morlet wavelet transform is proposed to make signal processing more accurate. Results show in the 15% to 85% loading stage, Type 3 and Type 4 signals are abundant in fiber reinforced mortar than plain mortar, while Type 7 and Type 9 signals are abundant in the 85% to 100% loading stage. According to the temporal localization characteristics of signal frequency quantified by each type of signals, it can be inferred that the fibers improve the toughness of concrete materials. It is also found the strengthening and toughening effect of steel fiber is more sensitive to fiber contents than that of polypropylene fiber. The ratio of Type 1 signals can be used as a warning against the final failure of materials while that of Type 5 signals can be used to evaluate the anti-cracking effect of fibers.

Funder

National Natural Science Foundation of China

Publisher

Walter de Gruyter GmbH

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://www.degruyter.com/document/doi/10.1515/mt-2021-2146/pdf

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