Wavelet Power and Shannon Entropy Applied to Acoustic Emission Signals for Corrosion Detection and Evaluation of Reinforced Concrete

Abstract

Acoustic emission (AE) signals detected from corrosion test on a steel reinforced concrete beam subjected to the coupling effects of corrosive wet-dry cycles and static load are analyzed by power spectral density, wavelet transform, and Shannon entropy. The degradation process of the corroded reinforced concrete beam can be divided into four stages on the basis of the accumulated event number (AEN). Due to the difference of material properties, steel reinforcement and concrete matrix have distinguished AE features. The time-frequency characteristics of AE signals can reflect the microstructural degradation mechanism of steel corrosion and concrete cracking. The corrosion evaluation entails investigating the evolution of the wavelet power mathematically by Shannon entropy. The frequency-entropy clearly exhibits the relative power distribution of AE signal in a certain frequency region. With the accumulation of steel corrosion and concrete deterioration, the increment of the overall entropy integration is considerably apparent. The variation of frequency-entropy curve reveals the corrosion revolution of the reinforced concrete members under static load, which is represented by a transforming from corrosion-induced micro cracking to load-induced localized cracking.

Department(s)

Civil, Architectural and Environmental Engineering

Comments

Financial support from the National Natural Science, Foundation of China under the grants of 52078332, U2006223 and 51925805, from the Natural Science Foundation of Hebei, Province under the grant of E2020402079, and from the Guangdong Provincial Key Laboratory of Durability for Marine Civil Engineering (SZU) under the grant of 2020B1212060074 is gratefully acknowledged.

Keywords and Phrases

Acoustic Emission; Corrosion; Reinforced Concrete; Shannon Entropy; Wavelet Power

International Standard Serial Number (ISSN)

2578-062X; 2578-0611

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2022 Engineered Science Publisher LLC, All rights reserved.

Publication Date

01 Jun 2022

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