Analysis of Acoustic Emission Signals Processed with Wavelet Transform for Structural Damage Detection in Concrete Beams

Abstract

Concrete beams are elements used in many civil structures; unfortunately, they can contain cracks that lead to the collapse of the structures if those defects are not detected early enough. In this article, a new method to determine the structural condition of concrete beams subjected to bending is proposed. In general, it is based on the processing of the acoustic emissions (AE) signals, which are generated during the application of a load, by using the mathematical tool called wavelet transform (WT). The sound of the internal energy/crack is recorded as a hit or AE signal event; then, those signals acquired as waveforms are post-processed with the continuous WT (CWT); then, the wavelet energy (WE) is calculated for each hit by using an adequate scale range and the most convenient mother wavelet. Thus, with this method, it is possible to determine the structural condition (healthy or damaged) of concrete beams subjected to bending just by calculating the WE of any hit at any time and, even more, it is possible to define more precisely the stage of the structural condition as a healthy condition, micro-cracks appearance, the manifestation of a principal crack (hit with the highest WE), propagation of the principal crack, and final rupture. This method is experimentally validated in the laboratory, and additionally, ultrasonic pulse velocity tests (UPVT) are performed for some specimens to confirm the change between healthy and damaged conditions. The results are promising in order to apply this effective method in concrete beams of real-life structures.

The efficiency of arrival time picking methods for acoustic emission source localization in structures with simultaneous damage mechanisms

“…The selection of a single frequency, however, may alter the frequency, resulting in a prolonged wavelength and earlier arrival time, thereby affecting the accuracy of the results. On the other hand, Complex Gaussian and Mexican hat wavelets can maintain a constant wavelength of the decomposed signal across various decomposition levels, as these wavelets have a fixed wavelength 13 .…”

Optimized Wavelet and Wavelet Packet Transform Techniques for Assessing Crack Behavior in Curved Segments of Arched Beam Bridges Spanning Rivers

“…where the wavelet packet coefficients c i j,k (t) can be obtained from Equation (12). Also, Equation (13) ensures that the wavelet packet functions are orthogonal.…”

“…Within the context of arched beams, the introduction of cracks can introduce high-frequency elements into the signal. Here, the WT thrives by adeptly capturing these high-frequency features, thereby establishing its efficacy in the detection and localization of cracks [13,14]. Its intrinsic time-frequency localization properties serve as a pivotal asset in singling out transient or localized crack attributes, a crucial step in distinguishing them from other signal constituents.…”

Revealing the Proximity of Concrete Specimens to Their Critical Damage Level by Exploring the Cumulative Counts of the Acoustic Emissions in the Natural Time Domain

“…Therefore, the AEs technique gradually became a valuable tool for scientists and engineers responsible for monitoring the deformation and integrity of structures made of concrete and other brittle structural materials, offering critical insight concerning the onset and extent of internal damage and, also, about the mechanisms responsible for the generation of the networks of micro-cracks developed in the interior of the loaded element. Indicatively, one could mention, for example, the works by Cha and Buyukozturk [ 4 ] and also the very recent ones by De Maio et al [ 5 ], Pranno et al [ 6 ], Machorro-Lopez et al [ 7 ], Kontoni et al [ 8 ] and Brahim et al [ 9 ].…”