Simulation and Analysis with Wavelet Transform Technique and the Vibration Characteristics for Early Revealing of Cracks in Structures

Abstract

Implementation of improved instruments is used to detect damage in an accurate manner and fully analyze its characteristics. An aluminum beam has been used in this work to identify cracks by using a vibration technique. The simulation of frequency response feature was conducted using a finite element model to provide average measures of intensities of vibration. Two forms of wavelet packet transform (WPT) entropies Shannon and log energy were applied to identify the position, width, and size of the crack. The results showed that with an increase in crack depth, the amplitude also increased at certain crack sizes and for all crack positions. For two crack depths of 1.6 mm and 0.16 mm having the same crack size and position 12 mm and 60 mm, respectively, a 4.5% increase in amplitude was observed at a crack depth of 1.6 mm. Moreover, the amplitude varied inversely with the position. A 12.6% increase in amplitude was observed at a crack depth of 1.6 mm rather than 0.16 mm, while both depths occurred at the same crack position (75 mm) and size (20 mm). Experimental validation was performed on a cantilever beam with one crack. The maximum absolute error found was 7.5% for the crack position and 9.1% for the crack size. With the increase in crack depth, the obtained results decrease the stiffness of a beam in a single crack case.

[Retracted] Key Technologies of Face Sensor Recognition Entry System for New Energy Vehicles Based on Particle Swarm Neural Network

“…In the formula, ω represents the inertia weight; c 1 and c 2 are learning factors; and r 1 and r 2 are random numbers between (0, 1). v t id and x t id are the velocity and position of particle i in the d-th dimension in the t-th iteration, respectively; p t id is the position of the individual extreme value of particle i in the d-th dimension; p t gd is the position of the 3 Journal of Sensors global optimal extreme value of the population in the d-th dimension [12].…”

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

“…These scenarios are identified in Figure 3. Regarding model verification, the applied WT and WPT were verified using the results of the experimental study presented by Abu-Hamdeh et al [49]. A minimal crack location was identified by analyzing the mode shapes affected by the crack, and [49] treated the uncracked beams as an experimental task.…”

“…Regarding model verification, the applied WT and WPT were verified using the results of the experimental study presented by Abu-Hamdeh et al [49]. A minimal crack location was identified by analyzing the mode shapes affected by the crack, and [49] treated the uncracked beams as an experimental task. Aluminum specimens were prepared, and their material properties were characterized as follows: the modulus of elasticity (E) was measured as 70 GPa, and the mass density (ρ) was determined to be 2700 kg/m 3 .Various crack positions and sizes were investigated using wire-cut machining.…”

An automatic image processing based on Hough transform algorithm for pavement crack detection and classification

“…Other scholars have used wavelet transform due to its efficacy in time-frequency transformations (Abu-Hamdeh et al, 2021;Guo and Vavilov, 2013;Li et al, 2014;Nigam and Singh, 2020;Vidal et al, 2016). Conversely, others used correlation techniques by merging images using the digital image correlation (DIC) (Christensen et al, 2021;Gehri et al, 2020;Hamrat et al, 2016).…”