LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A combination of wavelet packet energy curvature difference and Richardson extrapolation for structural damage detection

Photo from wikipedia

Abstract Marine structures are exposed to various destructive factors during their serviceability. Therefore, timely damage detection and repair of these structures at early stages can increase their service life and… Click to show full abstract

Abstract Marine structures are exposed to various destructive factors during their serviceability. Therefore, timely damage detection and repair of these structures at early stages can increase their service life and prevent economic and human losses as much as possible. In this study, a method is presented to identify the location of multiple damages in the piles of a dolphin pier. In the first step of the proposed method, based on a combination of the Wavelet Packet Energy Curvature Difference (WPECD) and the Richardson extrapolation, a damage index is introduced to accurately find the damage zone/damaged piles in the dolphin wharf. The energy curvature difference of the wavelet packet was obtained based on the vibrating signals of the structure. Using an image processing technique, in the second step of the method, the locations of damage were extracted via the WPECD method. The efficiency and capability of the proposed method was confirmed by numerical and experimental results. The exact geometry of the damages in the experimental model was initially scanned by a three-dimensional scanning device. Then, the scanned images were processed and imported into the numerical model as an input file. Finally, the results showed that the proposed method could discover multiple structural damages with acceptable accuracy.

Keywords: method; curvature difference; damage; energy curvature; wavelet packet

Journal Title: Applied Ocean Research
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.